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<HintBlock type="info">

This post is maintained by Bytebase, an open-source database governance platform that can manage Google Cloud SQL. We update the post gradually.

</HintBlock>

[Google Cloud SQL](https://cloud.google.com/sql/) is a popular database service from Google Cloud. It offers completely managed relational databases for MySQL, PostgreSQL, and Microsoft SQL Server with rich extension collections, configuration flags, and developer ecosystems. Apart from features, pricing is another core factor to consider when comparing it with other similar services like [AWS RDS](/dbcost/rds-pricing/) and [Microsoft Azure SQL Database](/dbcost/azure-sql-database-pricing/). Also, there are several discussions on Reddit related to the pricing of Google Cloud SQL, as shown in the figure below. These all point to the importance of understanding the structure of Google Cloud SQL pricing.

![reddit](/content/blog/understanding-google-cloud-sql-pricing/reddit.webp)

> Looking for exact numbers? See the [Cloud SQL pricing table](/dbcost/cloudsql-pricing/) — every machine type priced per month, sortable and filterable across regions, engines, and editions.

## Google Cloud SQL Pricing

Pricing for Google Cloud SQL is based on a pay-as-you-go model. Google Cloud SQL offers two editions: Enterprise and Enterprise Plus. These editions provide different levels of availability, performance, and data protection. The price varies among different instance types and regions:

- CPU and memory pricing
- Storage and networking pricing
- Instance pricing (only applicable to shared-core)
- License pricing (only applicable to SQL Server)
- Extended support pricing (only applicable to end-of-life major versions)

### CPU and Memory Pricing

For dedicated-core instances, you choose the number of CPUs and the amount of memory you want, up to 96 CPUs and 624 GiB of memory for Enterprise edition and up to 128 CPUs and 864 GiB of memory for Enterprise Plus edition. For Cloud SQL Enterprise Plus edition for SQL Server instances, you can also choose from performance-optimized machines (up to 128 CPUs and 864 GiB of memory) and memory-optimized machines (up to 16 CPUs and 512 GiB of memory).

Each edition offers several machine series. For MySQL and PostgreSQL, Enterprise edition comes in the general-purpose and N4 series (both priced the same), while Enterprise Plus comes in the N2 and C4A (ARM) series. Enterprise Plus charges roughly a 30% premium per vCPU and per GiB over Enterprise in exchange for a higher availability SLA, a data cache, and faster maintenance.

Pricing for CPUs and memory varies based on the following three primary factors:

- The volume of CPUs you choose
- The total memory you select
- The region where your instance is located

If you enable other services, the total cost may include those charges:

- Failover replicas pricing
- Read replicas pricing
- High Availability pricing

Read replicas and failover replicas are charged at the same rate as stand-alone instances. HA prices — exactly double the stand-alone rate — are applied for instances configured for high availability, also called regional instances.

The tables below list hourly rates for the Iowa (us-central1) region. Multiply by roughly 730 hours to get a monthly figure.

**Enterprise Edition (us-central1, Hourly)**

| Resource  | On-demand (USD)   | 1-year commitment | 3-year commitment |
| --------- | ----------------- | ----------------- | ----------------- |
| vCPUs     | $0.0413 per vCPU  | $0.030975         | $0.019824         |
| Memory    | $0.0070 per GiB   | $0.00525          | $0.00336          |
| HA vCPUs  | $0.0826 per vCPU  | $0.06195          | $0.039648         |
| HA Memory | $0.0140 per GiB   | $0.0105           | $0.00672          |

**Enterprise Plus Edition - N2 Machine Series (us-central1, Hourly)**

| Resource              | On-demand (USD)   | 1-year commitment | 3-year commitment |
| --------------------- | ----------------- | ----------------- | ----------------- |
| vCPUs                 | $0.0537 per vCPU  | $0.040275         | $0.025776         |
| Memory                | $0.0091 per GiB   | $0.006825         | $0.004368         |
| HA vCPUs              | $0.1074 per vCPU  | $0.08055          | $0.051552         |
| HA Memory             | $0.0182 per GiB   | $0.01365          | $0.008736         |
| Data Cache Storage    | $0.000219 per GiB | -                 | -                 |
| HA Data Cache Storage | $0.000438 per GiB | -                 | -                 |

The Enterprise Plus C4A (ARM) series is priced almost identically to N2 ($0.054 per vCPU, $0.009 per GiB).

In addition, Cloud SQL provides committed use discounts (CUDs) that grant discounted prices for continuous use of database instances in a particular region for a one-year or three-year term: 25% off for one year and 52% off for three years. CUDs only apply to CPU and memory pricing. For more information, review [Committed use discounts](https://cloud.google.com/sql/cud).

### Storage and Networking Pricing

Storage is billed per GiB per hour. The monthly figures below are for us-central1, assuming 730 hours:

| Storage Type         | Price                |
| -------------------- | -------------------- |
| SSD storage capacity | ~$0.17 per GiB/month |
| HDD storage capacity | ~$0.09 per GiB/month |
| Backups (used)       | ~$0.08 per GiB/month |

#### HA Storage Pricing (Monthly)

| Storage Type         | Price                |
| -------------------- | -------------------- |
| SSD storage capacity | ~$0.34 per GiB/month |
| HDD storage capacity | ~$0.18 per GiB/month |
| Backups (used)       | ~$0.08 per GiB/month |

#### Hyperdisk Balanced

| Resource   | Price                  |
| ---------- | ---------------------- |
| Capacity   | ~$0.115 per GiB/month  |
| IOPS       | ~$0.02 per IOPS/month  |
| Throughput | ~$0.08 per MBps/month  |

HA Hyperdisk Balanced doubles the capacity, IOPS, and throughput rates.

With Hyperdisk Balanced, you are billed for provisioned capacity, IOPS, and throughput independently. You are billed for the total provisioned capacity of your Hyperdisk Balanced volumes until you delete them. Hyperdisk Balanced charges a monthly rate for the provisioned IOPS and provisioned throughput (in MBps) in excess of the baseline values of 3,000 IOPS and 140 MBps throughput.

Note: Committed use discounts do not apply to storage or network prices.

### Network Egress Pricing

When network traffic leaves a Cloud SQL instance, the charge applied depends on the destination of the traffic, and in some cases, whether a partner is involved.

Internet egress is network traffic leaving a Cloud SQL instance to a client that is not a Google product, such as using a local server to read data from Cloud SQL.

| Destination | Price |
| --- | --- |
| Compute Engine instances and Cloud SQL cross-region replicas | Within the same region: free<br />Between regions within North America: $0.12/GiB<br />Between regions outside of North America: $0.12/GiB |
| Google Products (except Compute Engine and traffic to Cloud SQL cross-region replicas) | Intra-continental: free<br />Inter-continental: $0.12/GiB |
| Internet egress using Cloud Interconnect | $0.05/GiB |
| Internet egress (not using Cloud Interconnect) | $0.19/GiB |

IPv4 addresses: $0.01 per hour while idle.

### Instance Pricing

Instance pricing is only relevant for shared-core instances, which are available on Enterprise edition only. It is charged for every second that the instance is running with the activation policy being set to "always". For more details, see [Billing on partial seconds](https://cloud.google.com/sql/pricing#billing-partial-seconds).

| Machine Type | vCPUs  | RAM (GiB) | Price (us-central1)    |
| ------------ | ------ | --------- | ---------------------- |
| db-f1-micro  | Shared | 0.6       | $0.0105/hour (~$8/mo)  |
| db-g1-small  | Shared | 1.7       | $0.0350/hour (~$26/mo) |

HA doubles these rates. Note that shared-core machine types are not covered by the Cloud SQL SLA.

### License Pricing (for SQL Server)

SQL Server license pricing is based on the selected edition and is charged per core hour. Cloud SQL does not support bring-your-own-license, and committed use discounts do not apply to licenses.

| SQL Server Edition | Price per Core Hour (USD) |
| ------------------ | ------------------------- |
| Enterprise         | $0.47                     |
| Standard           | $0.13                     |
| Web                | $0.01134                  |
| Express            | $0                        |

Microsoft licensing requires a core license for each virtual CPU with a four-core minimum, so instances with fewer than 4 vCPUs are charged for SQL Server at 4 times the license rate. SQL Server instances are charged a 10 minute minimum for licenses; after 10 minutes, licenses are charged in 1 minute increments.

### Extended Support Pricing

Since May 1, 2025, instances running major versions that have reached end of life (EOL) are charged for extended support, in addition to regular instance pricing. For dedicated-core instances it is priced per vCPU per hour; for shared-core instances, per instance per hour. Committed use discounts do not apply to extended support prices. Refer to the [database version policies](https://cloud.google.com/sql/docs/db-versions) for the extended support timelines of Cloud SQL major versions.

## Tools for Estimating Google Cloud SQL Pricing Cost

Given the pricing complexity, there are tools to help you estimate pricing easily.

### Official Pricing Calculator

[Pricing Calculator](https://cloud.google.com/products/calculator) is the official tool from Google Cloud. It enables you to estimate Google Cloud SQL cost with different configurations. After selecting the database engine, enter required information such as the number of instances, instance type, and location, and click **ADD TO ESTIMATE** to generate the result.

![calculator](/content/blog/understanding-google-cloud-sql-pricing/calculator.webp)

### Cloud SQL Pricing Table

Our [Cloud SQL pricing table](/dbcost/cloudsql-pricing/) lists the monthly compute price for every machine type. You can switch region, database engine, and edition, and sort by any column to compare instances at a glance.

## Tips for Optimizing Google Cloud SQL Pricing Cost

As mentioned above, one of the biggest concerns raised by reddit discussions is how to optimize Google Cloud SQL cost. Here are some common tips:

- **Watch out the disk space**: Google Cloud SQL has a unique feature called [automatic storage increases](https://cloud.google.com/sql/docs/mysql/instance-settings). You should monitor the disk space to spot any abnormal disk increase.

- **Watch out the network egress cost**: The egress cost could be outrageous. Usually you should try to co-locate your app server with the database in the same region to avoid any cost. If that's not possible, you may consider aggregating request or batching data transfer.

- **Take advantage of committed use discounts**: Cloud SQL offers committed use discounts that give you a considerable discount for one-year / three-year commitment: 25% off for one-year commitments and 52% off for three-year commitments on CPU and memory resources.

- **Pick the right edition**: Enterprise Plus charges about a 30% premium per vCPU and per GiB. If you don't need its higher SLA, data cache, or faster maintenance, the Enterprise edition serves most workloads at a lower price.

- **Delete idle instances**: It is well known that idle or abandoned resources are one of the biggest sources of waste in cloud spending. To reduce your cloud cost, it is absolutely necessary to delete idle instances. Watch out for those ephemeral testing database instances.

- **Resize overallocated instances**: Over-provisioning resources is common for DBAs who are used to provisioning larger instances on-premises. However, it can lead to unnecessary spending when migrating to the cloud platform. The smart way to optimize your cloud cost is to identify your resource requirements and scale instances accordingly.

- **Consider Hyperdisk Balanced storage**: For workloads with varying I/O requirements, Hyperdisk Balanced offers independent scaling of capacity, IOPS, and throughput, potentially providing cost savings compared to fixed-performance storage options.

- **Upgrade off end-of-life versions**: Since May 2025, instances on EOL major versions pay an extended support surcharge on top of regular pricing. Upgrading to a supported major version removes it.

## Summary

Google Cloud SQL is a great choice for organizations that need a fully-managed relational database service. In order to get the best value for your money, it is essential to understand the pricing structure of Google Cloud SQL.

Besides optimizing cloud database cost, teams also want to make better use of the purchased databases. To achieve that, you can check out our open source project Bytebase. Bytebase supports 10+ OLTP, OLAP, NoSQL databases including all three Google Cloud SQL databases, MySQL, PostgreSQL, and SQL Server. It's an all-in-one platform for developers, DBAs, and platform engineers to manage the database development lifecycle efficiently and reliably. Go [self hosting](https://docs.bytebase.com/get-started/deploy-with-docker) with a single command to try it out.

![change-query-secure-govern-database-all-in-one](/content/blog/_shared/db-scheme-lg.png)



Database schema compare tool enables you to identify differences in the object structure within relational databases, and synchronize your specific objects across multiple databases. It is usually used in the following scenarios:

- Merge database changes from your private branch to your team's main branch
- Maintain schema consistency across homogeneous databases
- Build a new database test environment
- Deploy database schema changes to production based on application requirements
- Troubleshoot database problems when the service is down

**Quick pick:** for changelog-driven CLI workflows go with **Liquibase**; for declarative schema-as-code in CI/CD use **Atlas**; for a fine-grained desktop GUI use **MySQL Workbench**, **dbForge Schema Compare**, or **Navicat**; for team change management with review and one-click sync, use **Bytebase**.

## MySQL Workbench

[MySQL Workbench](https://dev.mysql.com/doc/workbench/en/) is the official GUI for MySQL development from Oracle. It includes schema comparison and synchronization utilities. It enables you to compare and synchronize schema between models, databases and SQL files. These three types can be the destination, source, or both. The following figure shows the source is model and the destination is database.

![workbench](/content/blog/top-mysql-schema-compare-tools/workbench.webp)

In addition, MySQL Workbench allows you to create a report showing the differences in catalog between the compared objects, as the next figure shows.

![report](/content/blog/top-mysql-schema-compare-tools/catalog-report.webp)

It is available on Windows, Linux and Mac OS X.

## dbForge Schema Compare for MySQL

[dbForge Schema Compare for MySQL](https://www.devart.com/dbforge/mysql/schemacompare/) is dbForge's flagship product for MySQL database development and management. It allows you to compare and synchronize database schema between databases and SQL files. dbForge Schema Compare for MySQL has two distinct advantages over other comparison tools:

- Diff and synchronize MySQL databases quickly and efficiently, even for extra-large ones
- Automate routine tasks via CLI to schedule your comparison and synchronization tasks

![dbforge](/content/blog/top-mysql-schema-compare-tools/dbforge.webp)

dbForge is only available on Windows.

## Navicat

[Navicat](https://www.navicat.com/) is a commercial cross-database GUI with strong MySQL support. Its Structure Synchronization feature compares two MySQL databases, shows the structural differences, and generates and executes the SQL to synchronize the target with the source. It also handles data synchronization and general database administration.

Navicat is a paid product for Windows, macOS, and Linux — a good fit for teams that want a full-featured commercial GUI, though it is heavier and licensed compared with a free option like MySQL Workbench.

## Liquibase

[Liquibase](https://www.liquibase.com/) is an open-source command-line tool that helps you track, version, and deploy database changes with declarative and imperative approaches. It provides three Diff-based commands to discover the differences between databases and database snapshots: `diff`, `diff-changelog`, and `generate-changelog`. You can refer to the section of [Database inspection commands](https://docs.liquibase.com/commands/home.html#database-inspection-commands) for more details. The biggest advantage of Liquibase's comparison feature is that it allows you to integrate it into various workflows.

![liquibase](/content/blog/top-mysql-schema-compare-tools/liquibase.webp)

## Atlas

[Atlas](https://atlasgo.io/) is an open-source schema-as-code tool that manages database schemas declaratively. You define the desired MySQL schema in HCL or plain SQL, and Atlas computes the difference against a live database and generates the migration needed to reconcile them — the `atlas schema diff` and `atlas migrate diff` commands compare a source and a target (databases, schema files, or migration directories) and emit the SQL.

Atlas is built for automation: it plugs into CI/CD, supports migration linting and pre-apply safety checks, and works across MySQL, PostgreSQL, SQLite, SQL Server, and more. It rewards teams that prefer to manage schema in version control rather than through a GUI. The trade-off is the learning curve of its declarative workflow and HCL dialect.

## Bytebase

[Bytebase](/) is an open-source database DevOps tool that is GitLab/GitHub for databases management throughout the software development lifecycle (SDLC). It offers a GUI web-based workspace for Developers and DBAs to collaborate safely and efficiently. Bytebase has a powerful comparison and synchronization feature with the following unique capabilities:

- Compare and synchronize schema from one database to multiple databases

![bytebase-source](/content/blog/top-mysql-schema-compare-tools/bytebase-source.webp)

- Allow you to select a schema version from the database change history as the source

![bytebase-target](/content/blog/top-mysql-schema-compare-tools/bytebase-target.webp)

- Provide a user-friendly way to display the differences between databases

![bytebase-diff](/content/blog/top-mysql-schema-compare-tools/bytebase-diff.webp)

- Enable you to complete the synchronization with one-click

![bytebase-issue](/content/blog/top-mysql-schema-compare-tools/bytebase-issue.webp)

Most schema compare features are available in Bytebase's Free plan.

## Summing it up

If you are comfortable with code-first tooling, Liquibase and Atlas are excellent choices for automating diffs in your pipeline. If you prefer fine-grained control during the synchronization process, there are GUI solutions like MySQL Workbench, dbForge Schema Compare for MySQL, and Navicat. On the other hand, if you need a fully-fledged GUI and a more streamlined experience to compare, review and deploy database schema changes, Bytebase will be a great fit.

## FAQ

**What is a MySQL schema compare tool?**

It is a tool that detects structural differences between two MySQL schemas — tables, columns, indexes, constraints, views, stored procedures, triggers — and generates the SQL to synchronize them. It's used to keep environments consistent and to promote changes safely.

**Which MySQL schema compare tool works best in CI/CD?**

Command-line and schema-as-code tools automate most cleanly: Liquibase fits scripted pipelines, Atlas offers a declarative CI/CD workflow with migration linting, and dbForge exposes a CLI for scheduled tasks. Bytebase layers GitOps-driven review and approval on top for team workflows.

**Are there free MySQL schema compare tools?**

Yes. MySQL Workbench and Atlas are free and open source; Liquibase has an open-source edition; dbForge and Navicat are commercial (dbForge is Windows-only); and most of Bytebase's schema-sync capability is available on its Free plan.



<HintBlock type="info">

This post is maintained by Bytebase, an open-source database governance platform. We update the post gradually.

</HintBlock>

This is a series of articles about database schema change / database schema migration:

1. [What is a Database Schema?](/blog/what-is-database-schema/)
1. [What is a Database Schema Migration?](/blog/what-is-database-migration/)
1. [How to Handle Database Migration / Schema Change?](/blog/how-to-handle-database-schema-change/)
1. Top Database Schema Migration Tools in 2026 (this one)

---

It's year ~~2024~2025~2026, database schema migration is still the riskiest area in application development - it's tough, risky, and painful. Database schema migration tools exist to alleviate pain, and have come a long way: from the basic CLI tools to GUI tools, from simple SQL GUI clients to the all-in-one collaboration database platform.

## Command-Line Clients (CLI) - mysql / psql

`mysql` and `psql` are the native CLI for MySQL and PostgreSQL respectively. You can send commands or queries directly to MySQL or PostgreSQL servers from the command line.

![_](/content/blog/top-database-schema-change-tool-evolution/mysql.webp)

Although the CLI interface is simple, sometimes it's intimidating to the beginners.

## GUI

### phpMyAdmin, pgAdmin

phpMyAdmin and pgAdmin are classic SQL clients. phpMyAdmin is already an established tool for managing MySQL and MySQL-compatible databases (e.g. MariaDB), while pgAdmin is the PostgreSQL counterpart, which has now evolved to pgAdmin 4. Compared with CLI tools, phpMyAdmin and pgAdmin provide a UI for running and executing SQL queries, making them user friendlier.

![_](/content/blog/top-database-schema-change-tool-evolution/gui.webp)

### DBeaver

DBeaver's initial release came in 2010, this open-source SQL client supports a whole range of databases (SQL, NoSQL, and cloud DBs), and keeps up with the latest trends in the AI realm by incorporating OpenAI's GPT-capabilities, allowing natural language to be converted into SQL. In 2025, DBeaver has expanded its AI capabilities with more advanced schema optimization suggestions and enhanced query performance analysis.

![_](/content/blog/top-database-schema-change-tool-evolution/dbeaver.webp)

### DataGrip

DataGrip is another commercial SQL client developed by JetBrains. DataGrip has powerful code completion and refactoring tools for efficient database development. The AI Assistant, which became a standard feature in 2025, supports text2sql, schema optimization, code explanation, and automated migration script generation with backward compatibility analysis.

![_](/content/blog/top-database-schema-change-tool-evolution/datagrip.webp)

### Navicat

Navicat was first released back in 2001. It only supported MySQL back then, but later added more databases. Although Navicat's UI looks a bit outdated, it has complete functionality and provides a smooth overall experience when operating databases. In 2025, Navicat introduced a modernized interface with improved cloud integration features.

![_](/content/blog/top-database-schema-change-tool-evolution/navicat.webp)

GUI based SQL client is a good complementary to CLI based sql client. Fundamentally, they work in the same way. You connect to the database, and execute some SQL. Quick and convenient, on the flip side, lack of control, both in terms of database change management and data security. This [post](/blog/bytebase-vs-navicat/) goes into more details using Navicat as an example.

## GitOps / Database-as-Code

To better manage and source control database schema changes, several tools have introduced the code change process into database changes, known as Database-as-Code.

### Liquibase

Liquibase started out in 2006 as an open-source library for tracking, managing and applying database changes. Fun fact: Liquibase was acquired by a company called Datical in 2012 and rebranded to Datical, but then changed their name back to Liquibase in 2020 (wise move, have you seen anyone mention Datical on a forum?).

![_](/content/blog/top-database-schema-change-tool-evolution/liquibase.webp)

Liquibase's main product is a Java-based CLI that allows developer teams to integrate database schema migration into their CI/CD workflows through the CLI. As of 2025, Liquibase has strengthened its enterprise offerings with enhanced security features and improved support for regulated industries requiring detailed change tracking.

### Flyway

Flyway shares similarities with Liquibase in many ways: they are both long-established, both have a customer base, and are open-source projects. Its core product is a CLI and a Java library.

The commercial entity behind Flyway is Redgate (acquired in 2019). It's got 3 editions: community, team and enterprise. You can tell that they have marked a clear boundary between the open-source and commercial offerings: Flyway's website feels more casual overall, while Redgate's way more professional.

![_](/content/blog/top-database-schema-change-tool-evolution/flyway-redgate.webp)

Liquibase and Flyway are neck and neck. The main difference lies in their respective positioning: Liquibase is more enterprise oriented, while Flyway is more developer oriented.

### Sqitch

Sqitch is a purely open-source project with no commercial offerings that's been on the market since 2012. It is pure CLI and does not have a UI.

![_](/content/blog/top-database-schema-change-tool-evolution/sqitch.webp)

Unlike Java-based Liquibase and Flyway, Sqitch is developed using Perl. In addition, Sqitch has its own philosophy on how to manage database schema changes: Liquibase and Flyway both use file naming conventions to order schema migrations (convention over configuration).

![_](/content/blog/top-database-schema-change-tool-evolution/schema-migration.webp)

While Sqitch adopts an explicit approach to allow user to specify the order in the sqitch plan.

![_](/content/blog/top-database-schema-change-tool-evolution/appschema.webp)

### Atlas

![_](/content/blog/top-database-schema-change-tool-evolution/atlas.webp)

Atlas is an open-source tool built by Ariga, and promotes the term "database schema-as-code".

You can tell that they have drawn lots of inspo from HashiCorp and dubbed itself "Terraform for Database Migrations" upon its first appearance on Hacker News. They also invented Atlas HCL based on HCL (HashiCorp Configuration Language).

Atlas uses the modern programming language Go (unlike Liquibase/Flyway, which uses Java), and centers around CLI (similar to Liquibase/Flyway/Sqitch), but it also has a lightweight UI. Atlas Cloud is a commercial offering of the open-source version.

## All in One: GUI + GitOps / Database-as-Code + Collaboration

### Prisma

ORMs like Prisma target the domain of how code interacts with data. Although this is more of a backend topic, Prisma is an ORM with frontend roots. Frontend engineers are probably not the most proficient in SQL. To lower the barrier for managing database schemas, Prisma invents their own DSL to define data models.

![_](/content/blog/top-database-schema-change-tool-evolution/prisma.webp)

DSL is state-based (declarative), which describes the end state of the database schema instead of incremental changes, which is different from Liquibase/Flyway/Sqitch. This way, Prisma is able to provide a more comprehensive view of database management throughout the entire application development cycle.

Prisma ORM is open source and free to use, and their Data Platform offers a cloud-based collaborative platform with some advanced features (it's clear that their ambition goes beyond just an ORM and schema migration tool).

### Bytebase

Bytebase is an open-source database DevSecOps tool, covering database management scenarios from changes, queries, security, to governance with a visual web-based collaboration workspace

**Visual change workflow**

![_](/content/blog/top-database-schema-change-tool-evolution/bytebase-issue.webp)

Bytebase provides a web-based UI where developers and DBAs can collaborate to work on database changes through the same interface.

**Database-as-Code**

To better accommodate the working habits of developers, Bytebase has integrated capabilities into [code repositories such as GitLab and GitHub](/blog/integrate-sql-review-into-github/). With the GitOps workflow enabled, developers can submit database change files to familiar code repositories, and once review is completed and committed to the repo, the deployment will be automatically triggered by Bytebase. No need to switch between multiple tools!

**Team Collaboration & Management**

You can define different [roles](https://docs.bytebase.com/concepts/roles-and-permissions/) for members at two levels: Workspace and Project. You can assign different roles to your team members, so that they have different permissions for different projects; or configure approval workflows for each project, such as specifying specific DBAs or QA responsible for this specific project.

![_](/content/blog/top-database-schema-change-tool-evolution/bytebase-roles.webp)

The difference between Prisma and Bytebase lies in the target audience. Prisma is mainly aimed at front-end/full-stack developers, while Bytebase is more focused on back-end and DBAs. Both products provide collaboration capabilities, with Prisma focusing on the collaboration between developers in a single project, while Bytebase targets the entire engineering organization, i.e. developers and DBAs / Platform Engineering / Ops teams. In 2025, Bytebase has enhanced its collaboration features and expanded its role-based permissions system to provide even more granular control for engineering organizations.

## To Sum Up

| Feature              | Liquibase | Flyway           | Atlas            | Prisma         | Bytebase |
| -------------------- | --------- | ---------------- | ---------------- | -------------- | -------- |
| Open Source          | ✅        | ✅               | ✅               | ✅             | ✅       |
| Commercial Offering  | ✅        | ✅               | ✅               | ✅             | ✅       |
| Web UI               | ❌        | ✅ (lightweight) | ✅ (lightweight) | ✅             | ✅       |
| Rollback Support     | ✅        | Limited          | ✅               | Limited        | ✅       |
| CI/CD Integration    | ✅        | ✅               | ✅               | ✅             | ✅       |
| Team Collaboration   | Limited   | Limited          | Limited          | ✅             | ✅       |
| Role-Based Access    | ❌        | ❌               | Limited          | Limited        | ✅       |
| Cloud-Native Support | Limited   | Limited          | ✅               | ✅ (expanding) | ✅       |

If you are operating the database as an individual, the classic CLI or GUI SQL clients like Navicat will suffice. If you prefer integration with code repos, there are solutions like Liquibase and Flyway. However, for a GUI and project collaboration capabilities similar to Jira or GitLab, your options are Prisma and Bytebase. And Bytebase is the only tool that offers organization-wide management capabilities to ensure data security and governance, in addition to making database changes more efficient and safer.

This wraps our database schema change series. Here at Bytebase, we are trying to deliver a schema change experience as close as to the code change experience, from both the individual perspective and the organization perspective. To give it a try, [start locally with a single command](https://docs.bytebase.com/get-started/deploy-with-docker/).



<HintBlock type="info">

This post is maintained by Bytebase, an open-source database governance platform. We update the post every year.

</HintBlock>

This is a series articles about SQL Clients / SQL Editors:

1. Open Source SQL Clients (this one)
1. [Text-to-SQL Query Tools](/blog/top-text-to-sql-query-tools/)

---

The best free, open-source SQL clients and database management software in 2026 are **DBeaver**, **Beekeeper Studio**, **DbGate**, **HeidiSQL**, and **Bytebase**. DBeaver is the most versatile, supporting 80+ SQL and NoSQL databases. Beekeeper Studio and DbGate offer the cleanest cross-platform experience. HeidiSQL is the long-standing tool for MySQL and MariaDB. Bytebase is a server-side tool that adds team access control, audit logging, and data masking on top of the SQL editor. All of them are free database software with no license fee: DBeaver, Beekeeper Studio, and DbGate run on Mac, Windows, and Linux, HeidiSQL is Windows-first (Linux via Wine), and Bytebase runs in the browser. (This list is multi-database by design. Single-database tools live in their own posts: Postgres-only editors like pgconsole in [top pgAdmin alternatives](/blog/top-pgadmin-alternative/), MySQL-focused tools like phpMyAdmin in [top MySQL GUI clients](/blog/top-mysql-gui-client/).)

When database systems debuted about 40 years ago, the only way to access or modify a database was through the command line, which was not only unintuitive but also prone to errors that could lead to major problems. As a result, people began developing tools with graphical user interfaces (GUIs), which became what we now know as SQL clients — essentially front-end applications for database services. Whether you need a free database management software for Mac, Windows, or Linux, these open-source SQL GUI tools offer powerful alternatives to commercial database clients. In this post, we are taking a look at some of the best free SQL client options for you to try.

## What to look for in an open source SQL client

Not every SQL client fits every team. When comparing open-source SQL clients and database management software, weigh these criteria:

- **Open source.** The code should be freely available and modifiable, so you can audit it, self-host it, and avoid vendor lock-in.
- **Multi-database support.** A single tool that speaks MySQL, PostgreSQL, SQL Server, Oracle, and NoSQL saves you from juggling one client per engine.
- **Cross-platform.** Native support for Mac, Windows, and Linux — or a browser-based UI — keeps the whole team on the same tool.
- **SQL editor quality.** Autocomplete, syntax highlighting, query history, and result export are the day-to-day features you actually live in.
- **Team collaboration and security.** For shared production access you need centralized credentials, access control, audit logging, and data masking — capabilities client-side desktop tools cannot provide.

## DBeaver

[DBeaver](https://github.com/dbeaver/dbeaver) is a veteran SQL client. In addition to basic visualization and management capabilities, it has a SQL editor, data and schema migration capabilities, monitor database connections, and more. It supports a full range of databases (both SQL and NoSQL). DBeaver is also hooked up with GPT-3, which converts your natural language to SQL.

![dbeaver](/content/blog/top-open-source-sql-clients/dbeaver.webp)

It's worth noting that DBeaver [announced](https://techcrunch.com/2023/04/11/dbeaver-takes-6m-seed-investment-to-build-on-growing-popularity/) a $6M seed round in April 2023 (the press release also mentions that DBeaver has over 8M users and 5,000+ paying subscribers), their first funding since the author built it in 2013.

The same team also maintains [CloudBeaver](https://github.com/dbeaver/cloudbeaver), a self-hosted web version of DBeaver — still a SQL workbench in the browser, without the team governance layer that Bytebase (covered below) provides.

## Beekeeper Studio

[Beekeeper Studio](https://github.com/beekeeper-studio/beekeeper-studio) is a modern (aesthetic) and lightweight SQL client that supports MySQL, Postgres, SQLite, SQL Server, etc. It is available on Linux, Mac and Windows.

![beekeeper](/content/blog/top-open-source-sql-clients/beekeeper.webp)

The author of Beekeeper Studio is an independent developer who started building this tool in 2019 because he couldn't find an easy-to-use cross-platform SQL client. After almost a year of hard work, the first version was released in early 2020.

## DbGate

[DbGate](https://github.com/dbgate/dbgate) works in Windows, Linux, Mac, and your web browsers without compromises in functionality. Both SQL and noSQL databases are supported, from MySQL, PostgreSQL, SQL Server, MongoDB, SQLite, to CockroachDB.

![dbgate](/content/blog/top-open-source-sql-clients/dbgate.webp)

The author of DbGate [says](https://news.ycombinator.com/item?id=26899100) this was his passion project because he couldn't find a SQL client for Linux. He had built SQL clients for Windows in the past, so this was influenced by his own work experience.

## HeidiSQL

[HeidiSQL](https://github.com/HeidiSQL/HeidiSQL) is also a lightweight SQL client that supports a long list of databases including MariaDB, MySQL, MS SQL, PostgreSQL, SQLite, Interbase and Firebird. In addition to basic SQL client functionalities, users can export structures and data to SQL files or copy them to the clipboard or other servers.

![heidisql](/content/blog/top-open-source-sql-clients/heidisql.webp)

The codebase for HeidiSQL [originally came from](https://www.heidisql.com/forum.php?t=20155) the author's own MySQL-Front 2.5 software, but he later sold the MySQL-Front brand and the author renamed his project HeidiSQL and has maintained it to this day.

## Bytebase

Aforementioned tools are all SQL editors built for individual use — even the browser-based ones mostly move the same single-user editor onto a server. What if you want a SQL client for team use? The individual-oriented SQL editors would not be sufficient because for team use, it would require:

- **Centralized access control**. Ideally you don't want to give away production database credentials to developers by default and only allow them to requst on demand.
- **Audit logging**. You want to capture all operations performed on the database.
- **Request and review workflow**. You want users to go through a ticketing process to request the access rights.
- **Data masking**. You may want to prevent users seeing sensitive data.
- **Policy as Code (GitOps)**. Permission control and masking policies can be codified with Terraform and integrated with your existing DevOps pipeline.

All above requirements call for a server-side solution. And that's what [Bytebase SQL Editor](/sql-editor/) provides.

![bytebase-sql-editor](/content/blog/top-open-source-sql-clients/sql-editor.webp)

## SQL Client Comparison Table

| Tool             | Platform                 | Database Support                                | Best For                                   |
| ---------------- | ------------------------ | ----------------------------------------------- | ------------------------------------------ |
| DBeaver          | Mac, Windows, Linux      | 80+ databases (SQL & NoSQL)                     | Power users needing broad database support |
| Beekeeper Studio | Mac, Windows, Linux      | MySQL, Postgres, SQLite, SQL Server             | Developers wanting a clean, modern UI      |
| DbGate           | Mac, Windows, Linux, Web | MySQL, PostgreSQL, SQL Server, MongoDB, SQLite  | Cross-platform use including web browsers  |
| HeidiSQL         | Windows (Linux via Wine) | MySQL, MariaDB, SQL Server, PostgreSQL, SQLite  | Windows users managing multiple databases  |
| Bytebase         | Web-based (server-side)  | MySQL, PostgreSQL, SQL Server, Oracle, and more | Team collaboration with access control     |

## Frequently Asked Questions

### What is the best open source SQL client?

DBeaver is the most widely used open-source SQL client because it supports 80+ SQL and NoSQL databases on Mac, Windows, and Linux. For a lighter, more modern interface, Beekeeper Studio and DbGate are strong alternatives. For team use with access control and audit logging, Bytebase is the server-side option.

### Are open source SQL clients really free?

Yes. DBeaver (Community Edition), Beekeeper Studio, DbGate, HeidiSQL, and Bytebase (Community Plan) are all free and open source. Some sell paid editions with extra features, but the core tools remain free — install the desktop clients directly, or self-host the web-based ones.

### What is the best free database management software for Mac?

DBeaver, Beekeeper Studio, and DbGate all run natively on macOS and are free to use. Beekeeper Studio is often preferred on Mac for its clean, native-feeling UI, while DBeaver wins on breadth of database support.

### What is the difference between a SQL client and database management software?

A SQL client is a desktop or browser GUI that an individual uses to run queries and browse data. Database management software is a broader category that also covers team-oriented capabilities — centralized access control, change review, audit logging, and data masking. Tools like DBeaver serve the individual; a server-side tool like Bytebase serves the team.

### Which open source SQL client is best for teams?

Client-side editors give every developer direct database credentials, which is risky for shared production databases. For teams, a server-side tool like Bytebase adds centralized access control, request-and-review workflows, audit logging, and data masking so you can grant query access without handing out production passwords.

## Summary

We briefly looked at the history of a handful of SQL Clients to understand some of the more famous open source solutions, rather than comparing the product or their functions (I mean, after 20 years of refinement those veteran SQL clients can't be too bad, right?). It seems that most of the authors began building because they were unable to find a product that fit their needs perfectly, but the story afterwards is very different: some tools were then commercialized, some continued on with a strong community, and some gradually faded out due to a change of focus.

And we wonder, with the popularity of ChatGPT, will there be more open source SQL clients like SQL Chat based on Chat interaction?

Beyond using the general SQL Client to interact with the databases, developers and DBAs also adopt more specialized tools for particular tasks:

- To perform schema migrations, go check out [Top Database Schema Migration Tools](/blog/top-database-schema-change-tool-evolution/).
- To compare and synchronize database schemas, go check out [Top MySQL Schema Compare Tool](/blog/top-mysql-schema-compare-tools/).
- For Postgres, go check out [Top Postgres GUI client](/blog/top-postgres-gui-client/).
- For MySQL, go check out [Top MySQL GUI client](/blog/top-mysql-gui-client/).



Bytebase is a Database CI/CD tool for DevOps teams. It currently supports 10+ databases including MySQL, PostgreSQL, Redis, and MariaDB. From development to testing, we need to deploy several different kinds of database instances, which can be rather time-consuming and labor-intensive if deployed one by one.

There are a handful of tools on the market to spin up local database instances quickly, and folks on my team have recommended several free tools, so I thought I'd do a round-up.

Some background info: I'm not a dev (am a developer-marketer, I would test/try out new features before they are rolled out) and I use a Mac.

## DBngin

[DBngin](https://dbngin.com/) currently supports PostgreSQL, MySQL and Redis. And it supports certain different versions of the same database, and can also run multiple versions of database instances on multiple ports at the same time, very convenient for testing!

![dbngin-ui](/content/blog/local-db/dbngin-ui.webp)

DBngin is [open source](https://github.com/TablePlus/DBngin), and they belong to the organization TablePlus (database GUI tool), which means DBngin can be connected to TablePlus, and you can visually manage your local databases.

![dbngin-free](/content/blog/local-db/dbngin-free.webp)

## Postgres.app

[Postgres.app](https://postgresapp.com/), as the name (and logo) implies, only supports Postgres.

![postgresapp-db](/content/blog/local-db/postgresapp-db.webp)

It's actually a complete PostgreSQL installer that packages Postgres into a standard Mac app, and it's perfectly fine if you don't know how to use the command line, because there's a super simple UI. So if you want to run PostgreSQL on your Mac, this is the one.

Postgres.app is also [open source](https://github.com/PostgresApp/PostgresApp) with active development.

## StackBricks

[StackBricks](https://stackbricks.app/) supports MariaDB (points for being the only tool in this round-up that supports MariaDB!), MySQL, PostgreSQL and Redis, and a wide range of their versions, as well as the ability to start multiple local databases on multiple ports.

![stackbricks](/content/blog/local-db/stackbricks.webp)

StackBricks is not open source (but still free to use), but there is [an Issue Tracker](https://github.com/tpetry/stackbricks-community) for your feature requests.

## My Thoughts

For me, as long as the tool suffices for testing purposes, I don't really have high requirements for performance, I would say a simple and easy-to-use UI & multiple database support are the differentiators. In fact, I have been using DBngin, but I tried StackBricks for the sake of writing this post, and it looks like StackBricks is quite good, so I'm gonna try it out for a while.

How do you spin up local database instances for testing?



💡 This article is a compilation of this discussion on Reddit: [Do DBAs impose strict requirements for database schema conventions at your org?](https://www.reddit.com/r/ExperiencedDevs/comments/xcswje/do_dbas_impose_strict_requirements_for_database/)

![_](/content/blog/is-sql-review-necessary/reddit.webp)

## Background Info

The author’s team was developing new microservices and they needed to store data in SQL tables. These tables are wholly owned by the microservice and data from them is only being exposed via an API. He gave 2 examples of DBAs requesting “unnecessary” restrictions that “can potentially cause confusion down the road”, so the question is, are strict requirements on database schema really necessary?

## DingBat99999 (30 ⬆)

Maybe I'm missing something but none of the things your DBAs have requested seem unreasonable.

When it comes to constraints, in my experience, there's typically some discussion as to whether they're enforced in the application or in the database. Was there some historical decision there?

I mean, you could always tell the DBAs shirt size is implementation dependent and dynamic. Then they'd have no reason to ask for a constraint. Otherwise, YAGNI.

**💬Reply**

Enforcing the enum constraint in the database is a good practice and it sounds like you are privileged to work with a competent DBA. Strict data checking in your persistence layer is the surest way of preventing garbage from entering your system

## ccb621 (12 ⬆)

Take all of this energy, and ask the DBAs why these changes are important. If the don't already have one, volunteer to help them write a guide for to help future teams avoid this toil.

The changes seem nitpicky on the surface, but there could be a lot of hard-learned lessons below the service that warrant this level of review.

## nutrecht (7 ⬆)

I think it's totally normal to have standards for DB schema's you need to adhere to. I've seen those before. I've also seen the mess that happens when developers just do whatever the heck they want, so I can't really blame them.

So both things, the enum and the naming, sound reasonable to me. The benefit of the enum constraint in the DB is that you can never somehow end up with 'broken' data that breaks your software. I've had to deal with 'test' databases where testers directly inserted data and it was a pain in the ass to deal with.

So there are good arguments for both sides. I personally would not spend _any_ energy fighting this. Especially since you're probably going to need this DBA team somewhere down the line.

Also as a Java/Spring developer; you should work schema first. If you need to adapt a schema 'because of Spring' it generally just means you're doing something wrong.

## ViperRT10Matt (6 ⬆)

Our DBAs do not perform any functions like this. They release and manage what the developers give them. In terms of requiring changes to schemas or table designs, they function like stability control in a car; only intervening in extreme conditions to head off a truly dangerous situation.

## AdrianC9 (3 ⬆)

I work at a mid/large tech company, we do have "DBAs" (don't think they are traditional DBAs) that review database changes, however most standards are published in a wiki that should reviewed before subbitting db changes. So typically you know what to expect. As an example, we do require tables to be named in singular form, eg "tshirt" exactly for the reason you described. The ORM can then easily map everything correctly.

In regards to the db constraints, a lot of DBAs will often prefer this since it puts more control in their domain. Personally I agree that throwing things that are arguably business logic into the database is not ideal, and may result in issues in the future. That said, it's really not that big of an issue, and whenever it does break due to a conflict you can just point to that requirement.

## nderflow (2 ⬆)

The column constraints in particular are important. I've seen a company lose teens of thousands of customers and lose millions because they disabled the column constraints they already had.

The fact that a database can enforce integrity rules is one of the beauties of the modern relational database.

## check-himu (2 ⬆)

The plural convention is something we also follow and I don't have very strong feelings either for or against it. However, from experience, I will tell you that enforcing constraints in DB can be extremely helpful. With changes in code, there is always a chance of a bug that lets data you didn't want pass through. A final check at DB helps you avoid that scenario and having to do data fix later on.

## db-master (2 ⬆)

It's a common practice to enforce some level of consistency. Many hours can be saved if the engineering org can agree on the same ID format, first name, last name format and etc.

FWIW, there are tools like [GitHub SQL Review Action](https://github.com/marketplace/actions/sql-review) to enforce schema consistency in the CI/CD process.

## Our Take on SQL Review

Bytebase has built-in [SQL Review](https://docs.bytebase.com/sql-review/review-policy) capabilities that are customizable to check for issues in the schema change process. To better accommodate developers' workflow, we also [integrated SQL Review with GitHub](/blog/integrate-sql-review-into-github/), allowing you to manage SQL scripts in your GitHub repos and perform SQL Review there. This eliminates the need to switch between multiple tools and, more importantly, allows SQL Review to be conducted at the PR stage rather than waiting until the deployment stage.

That being said when it comes to database schema changes, the advice is simple: don't ask. If a DBA says so, just do it!

Last but not least - this article is a mere compilation of this [discussion](https://www.reddit.com/r/ExperiencedDevs/comments/xcswje/do_dbas_impose_strict_requirements_for_database/), don't miss out on the best practices and ideas colliding in the comment area ⚡️.



ChatGPT has only been around for less than half a year and we already cannot live without it. We wonder if ChatGPT can help us in the field of database administration, and we dug deep into some toolings that have incorporated ChatGPT to make our life easier.

## sqlTranslate

When it comes to databases, the first thing that comes to mind is whether ChatGPT can help us write SQL. [sqlTranslate](https://www.sqltranslate.app/) is a very simple tool that uses the OpenAI API to obtain the corresponding SQL statement by inputting natural language, or vice versa. You can also upload your own schema. Since it open-sourced three weeks ago, it has already gotten 2.6k stars and is [described by GitHub](https://twitter.com/github/status/1637937834865704960/photo/1) as an "incredibly useful weekend project". Looks like people have been suffering from SQL for way too long.

![_](/content/blog/chatgpt-enhanced-database-tools/sqltranslate.webp)

## AI2sql

[AI2sql](https://www.ai2sql.io/) is an AI-driven SQL query generator that has been around since 2021, and has recently incorporated OpenAI's GPT-3. Now engineers and non-engineers can write SQL easily without knowing the syntax. AI2sql is more comprehensive than sqlTranslate. The features include SQL syntax checking, formatting, and query generation, the databases supported covers the most popular ones on the market (such as MySQL, PostgreSQL, MongoDB, Oracle, etc.).

![_](/content/blog/chatgpt-enhanced-database-tools/ai2sql.webp)

## Aoi (葵)

[Aoi](https://github.com/shellfly/aoi) is a ChatGPT-driven dialogue agent program that can conduct natural language conversations with AI in your Terminal, and it can also be connected to your database to perform SQL tasks.

![_](/content/blog/chatgpt-enhanced-database-tools/aoi.webp)

## Bytebase

Bytebase is a database CI/CD tool that covers the entire life cycle of database development, and its SQL editor has also incorporated OpenAI's gpt-3.5-turbo in [its recent release](https://docs.bytebase.com/changelog/bytebase-1-14-0), where you input natural language and have it converted to SQL. Stay tuned for a more advanced version chat bot 🤖️!

![_](/content/blog/chatgpt-enhanced-database-tools/bytebase-sqleditor.webp)

## DBeaver

As a veteran SQL client, in addition to visualization and management capabilities, [DBeaver](https://dbeaver.com/) also has a SQL editor, along with data & schema migration capabilities, and database connection monitoring. In early February, DBeaver also incorporated GPT-3 to have AI convert natural language to SQL. For instance, you can ask for "all invoices from Germany with a total of more than 4", or in German, "Zeig alle Rechnungen aus Deutschland mit der Gesamtsumme über 4," and it will automatically convert the request into a query.

![_](/content/blog/chatgpt-enhanced-database-tools/dbeaver.webp)

## OSSInsight

In a sense, [OSSInsight](https://ossinsight.io/) has been helping you write SQL since way before.

![_](/content/blog/chatgpt-enhanced-database-tools/ossinsight.webp)

But recently they embraced OpenAI and launched a new tool called "Data Explorer", making it easier to explore GitHub data. You can ask whatever interests you in plain language, and AI will generate SQL for them (and then query it).

![_](/content/blog/chatgpt-enhanced-database-tools/rust-or-go.webp)

The database behind OSSInsight is TiDB, and TiDB Cloud recently also launched an intelligent data exploration feature using OpenAI: [Chat2Query](https://www.pingcap.com/chat2query-an-innovative-ai-powered-sql-generator-for-faster-insights/), which is another tool that generates SQL queries based on your input and then queries and visualizes the database for you.

## Outerbase

_Outerbase has been [acquired by Cloudflare](https://blog.cloudflare.com/cloudflare-acquires-outerbase-database-dx/) in 2025_

[Outerbase](https://outerbase.com/) is a new tool that was officially released on Feb.15, 2023. Compared with traditional database management tools, Outerbase completely conforms to current aesthetics. Its user experience is similar to that of an Excel spreadsheet, and it uses GPT-3 to help users write SQL queries and generate dashboards, making it useful for both developers and data analysts.

![_](/content/blog/chatgpt-enhanced-database-tools/outerbase.webp)

## To wrap up

It looks like using ChatGPT to enhance data management and analysis for your databases is gonna be an SOP in the database industry. Of course, these tools are just the tip of the iceberg, and their integration with ChatGPT is still in its early stages. However, it is clear that the benefits of combining ChatGPT with database management tools are enormous. Moreover, besides text2sql, ChatGPT can be used in many other database-related fields, such as customer support, query assistance, database management, and data analysis (you can also consult ChatGPT about what else it's capable of).

DBAs: get ready to retire officially. Just kidding, but perhaps the long-established SQL clients such as Navicat are already feeling a bit nervous.



## First Encounter

The other day, I stumbled across [motherduck.com](https://motherduck.com). The website was rough.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/motherduck-old.webp)

While with an all-star team.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/motherduck-team.webp)

From its slogan "Data Infrastructure and Analytics" and the team background, I guessed they want to challenge Snowflake and/or Databricks. But how? Building yet another cloud-native warehouse with claimed performance/price benefits is meh. And MotherDuck is quite unusual name. Why would they choose it?

Today, after reading their [funding post](https://motherduck.com/blog/announcing-series-seed-and-a/) (together with an expected website redesign), I now have a better understanding to answer those questions.

## Naming

The name MotherDuck comes from [DuckDB](https://duckdb.org/), the SQLite for Analytics. MotherDuck commercializes the open-source DuckDB, which is a standard infra startup playbook nowadays.

## Manifesto

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/manifesto.webp)

I was confused by the serverless part at first. Though serverless is a much-abused word, most people would still pair serverless with cloud. MotherDuck markets itself as serverless, on the other hand, it says not to wait for the cloud, and then they probably would still offer a cloud service (who wouldn't?).

In common sense, serverless means there are still servers that are masked by the cloud service providers. Servers exist, users just don't need to care about them. While MotherDuck's serverless is a different thing, there is no server at all, apparently, since the underlying DuckDB is just a library to be embedded instead of a server on its own.

## Democratizing Data

Snowflake brings the novel idea to separate the compute from storage, this architecture innovation grants it a huge competitive edge over the years. While from the product perspective, they are still tightly coupled since the data is locked in the Snowflake platform.

MotherDuck is different. Say you have a single data file, Parquet, CSV, SQLite or whatever format, that file resides on your local disk, S3, GitHub or anywhere. Then you use MotherDuck to mount that file from the computing environment of **YOUR CHOICE**, now you have a powerhouse ready to analyze that file. Because MotherDuck's zero dependency (thanks to SQLite-inspired DuckDB), it just takes seconds to acquire the MotherDuck binary (and even this will be eliminated after the pre-built distro includes it).

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/snowflake-vs-motherduck.webp)

While Snowflake separates the compute from storage, MotherDuck taps the compute into the storage. With MotherDuck, as long as you can access the data file, you have the data powerhouse, and beyond that data powerhouse, you can build data solutions.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/ossinsight.webp)

Take a real example, [OSSInsight](https://ossinsight.io/), a site to ingest GitHub events in real-time and offer insights. While its tech stack has already been [simplified by adopting TiDB](https://ossinsight.io/blog/why-we-choose-tidb-to-support-ossinsight/), the future MotherDuck could probably deliver a similar version with an even simpler stack.

**Because with MotherDuck, all application runtime artifacts can be captured in a single file.**

This is not a new idea though. The legendary [Hypercard](https://en.wikipedia.org/wiki/HyperCard) introduced this, to store a self-contained application and data into a single file.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/hypercard.webp)

Also, the long-standing [FileMaker Pro](https://en.wikipedia.org/wiki/FileMaker), where the entire app and data are stored in a single .fmp12 file.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/filemaker.webp)

Yet MotherDuck could bring this idea to a new level, being capable of processing terabytes of data efficiently, defining open protocols among Dataset/MotherDuck Engine/MotherDuck Platform, integrating with GitHub to promote collaboration and etc.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/snowflake-or-motherduck.webp)

Immediately, MotherDuck starts competing with Snowflake on all fronts. Data teams still need [Fivetran](https://www.fivetran.com/) to move the data around, [dbt](https://www.getdbt.com/) to transform the data back and forth, even [meltano](https://meltano.com/) to assemble the platform, but for every analytic task, they will have to decide where to run it from, the Snowflake Cloud or the whatever computing environment at hand with MotherDuck.

And in the long horizon, it's all uncharted. MotherDuck could unleash all kinds of new data solutions. Only sky is the limit.

![_](/content/blog/motherduck-from-sqlite-to-the-docker-for-data/snowflake-next.webp)

MotherDuck's idea is novel, also the timing is perfect. The data analytics space is waiting for the next paradigm shift. While practitioners are content with better Snowflake alternatives, visionaries demand more. Instead of competing on the performance/cost frontier, MotherDuck chooses a different battleground, very wisely.

## Parting Thought

People give away the data to Snowflake alike for the processing power. With MotherDuck, they can acquire similar processing power while still controlling the data themselves. They can keep the data wherever they want, share it with whoever they like, and use it whenever they need.

**While Docker has become the runtime and standard to make applications universally accessible, MotherDuck could become the runtime and standard to make data universally accessible.**

And this time, MotherDuck must be better prepared than [Docker, Inc](https://www.infoworld.com/article/3632142/how-docker-broke-in-half.html), to get the lion's share if the vision is realized. Good luck team MotherDuck and just wondering would `Ducker` make a better name :)



This is a series of articles about database version control and database-as-code (GitOps)

1. [What is Database Version Control?](/blog/database-version-control/)
1. [Database Version Control, State-based or Migration-based?](/blog/database-version-control-state-based-vs-migration-based/)
1. [Database as Code - the Good, the Bad and the Ugly](/blog/database-as-code/)
1. The Database as Code Landscape (this one)
1. [Database Version Control Best Practice](/blog/database-version-control-best-practice/)

---

The idea of codifying database schema changes (aka schema migration) is not new. Many engineering teams have employed Liquibase / Flyway to adopt this practice. At the same time, we are observing an accelerated trend of embracing [Database as Code (DaC)](/blog/database-as-code/) across the industry. Several innovative products have also emerged to challenge the incumbents.

In this blog, we will review the state-of-the-art in the Database as Code landscape and share our own insight into the current and future trends in this space.

## The Overview

## The Gatekeepers

### Liquibase

Started in 2006, Liquibase is arguably the most well-known product in this segment. When someone asks for database schema change advice on a forum, oftentimes, you will see a reply mentioning Liquibase.

![_](/content/blog/database-as-code-landscape/liquibase-overview.webp)

Liquibase is both an open source project as well as a company providing its commercial offering. The company used to be called Datical, and was renamed Liquibase to consolidate the branding (wise move).
Liquibase main product is a Java-based CLI. Via the CLI, developer teams can integrate the database schema migration into their CI/CD workflow. For the Java application, Liquibase can also be used as a library. Applications usually embed Liquibase library to apply any applicable schema migration on startup.

In Liquibase, a schema migration unit is encapsulated in a `Change Set`. Probably due to its age and root in Java, the most commonly used form is XML (YAML and JSON support have been added later):

![_](/content/blog/_shared/liquibase-xml.webp)

Plain SQL is also supported with proper annotation:

![_](/content/blog/_shared/liquibase-sql.webp)

Liquibase is [migration-based](/blog/database-version-control-state-based-vs-migration-based/). It records the incremental change instead of the desired end state of the target database schema.

Recently, Liquibase introduced HUB, it's an information portal for paid customers to view, organize and monitor database change activity in real-time.

![_](/content/blog/database-as-code-landscape/liquibase-hub.webp)

### Flyway

![_](/content/blog/database-as-code-landscape/flyway-overview.webp)

Flyway resembles Liquibase in many ways. It's an open source project with a long history and a large customer base. Its core product includes the CLI and a Java library. Flyway also recently announced a web portal named Hub.

The commercial entity behind Flyway is Redgate through an acquisition. The branding may cause some confusion, while it also sets a boundary between the open source and commercial offering. Flyway carries a more casual branding tone:

![_](/content/blog/_shared/flyway-migration.webp)

Flyway website is not as shining as those new DevTools companies using sophisticated gradients. You can even spot some basic UI spacing issues. Yet Flyway shows a classic example that content matters more than cosmetic beauty and its documentation stands out because of the clarity.

Liquibase and Flyway are neck and neck. The major difference lies in their respective positioning. Liquibase caters to enterprise customers, while Flyway feels more accessible to the developers.

## Sqitch

Sqitch is also an open source project been on the market for a while. Sqitch is pure CLI-based and has no UI. Unlike Java-based Liquibase/Flyway, Sqitch is developed in Perl.

![_](/content/blog/database-as-code-landscape/sqitch-overview.webp)

Choosing Perl is not the only interesting aspect. Sqitch has its own design philosophy about how to manage database schema changes. Both Liquibase and Flyway use the file naming convention to control the schema migration behavior (convention over configuration):

![_](/content/blog/database-as-code-landscape/flyway-migration-version.webp)

While Sqitch takes an explicit approach. In the below example, you need to name the schema migration as `appschema`:

![_](/content/blog/database-as-code-landscape/sqitch-migration.webp)

If you later want to apply another migration depending on `appschema`, you need to supply with `--requires`:

![_](/content/blog/database-as-code-landscape/sqitch-migration-dependency.webp)

Sqitch also provides the unique tag and bundle command for the schema change deployment, which grants teams more power to wire the schema deployment into the application development lifecycle.

## The Starlets

### Atlas

![_](/content/blog/database-as-code-landscape/atlas-overview.webp)

Atlas is a new database schema migration tool that debuted recently. It takes traits from existing tools:

- It resembles Liquibase / Flyway / Sqitch in that it's mainly CLI focused, though it also has a lightweight UI to visualize the schema.
- It resembles Prisma in that it designs its own Domain Specific Language (DSL) to define the database schema. Originally, it chooses the same state-based approach as Prisma, but looks like it also added the migration-based approach.

![_](/content/blog/database-as-code-landscape/atlas-migration.webp)

- It's also heavily influenced by HashiCorp Terraform, using Go and inventing its own DSL. They even debuted as Terraform for Database Migrations on Hacker News:

![_](/content/blog/database-as-code-landscape/atlas-terraform.webp)

Altas current focus is on CLI. While stacking it against existing CLI tools like Liquibase / Flyway, it has the advantage of employing a modern programming language (Go instead of Java), and learnings from tools like Terraform and Prisma.

## The ORMs

Database schema migration is an integral part of the application development, thus it's no surprise popular application frameworks and ORMs provide the built-in schema migration capabilities:

- [Ruby on Rails Active Record Migrations](https://guides.rubyonrails.org/active_record_migrations.html) (Ruby)
- [Django Migrations](https://docs.djangoproject.com/en/4.0/topics/migrations) (Python)
- [MyBatis Migrations](https://mybatis.org/migrations) (Java)
- [GORM Migrations](https://gorm.io/docs/migration.html) (Go)

Though database schema migration falls into the backend category, the most recent innovation comes from Prisma, an ORM with a frontend root.

### Prisma

![_](/content/blog/database-as-code-landscape/prisma-overview.webp)

Node.js unlocks the pandora box for frontend engineers to build full-stack applications. We call it pandora box because it brings both prosperity and chaos. Full-stack applications consist of 3 pieces:

1. The code (stateless part).
1. The data (stateful part).
1. And how the code interacts with the data.

To a typical frontend engineer wanting to build a sustainable full-stack application, TypeScript / Express.js is solving the code problem. NoSQL databases like MongoDB are solving the data problem. Prisma is targeting the last problem of wiring code with data.

For frontend engineers, usability and accessibility are especially important. They are used to perfect pixels and HCI, and are not versed in composing SQL. To lower the barrier of managing database schemas, Prisma specifically designs a DSL:

![_](/content/blog/database-as-code-landscape/prisma-schema.webp)

The DSL takes the state-based approach (declarative), in that the DSL describes the desired end state of the targeting database schema instead of the incremental changes. This is different from Liquibase / Flyway / Sqitch.

Prisma also invests heavily in the integration and development workflow.

![_](/content/blog/database-as-code-landscape/prisma-stack.webp)

![_](/content/blog/database-as-code-landscape/prisma-lifecycle.webp)

Unlike its backend ORM peers, Prisma takes a refreshing approach and offers a more holistic view of managing database data and schema throughout the application development lifecycle.

![_](/content/blog/database-as-code-landscape/prisma-product-line.webp)

By looking at their product line, you can easily tell their ambitions are definitely not limited to being an ORM and schema migration tool.

## The Database

All tools described above work with many different database systems. While the application of Database as Code is database agnostic, there emerge new database systems promoting developer experience as a key differentiator. This developer-centric perspective as well as features like branching / cloning aligns with the mindset behind Database as Code.

### PlanetScale

![_](/content/blog/database-as-code-landscape/planetscale-overview.webp)

PlanetScale used to be a Vitess hosted service. They pivoted last year to focus on the developer workflow. Though you may still come across some Vitess footprint on their website, most new materials are talking about database development workflow features such as branching, online schema change, and the recently introduced rewind:

![_](/content/blog/database-as-code-landscape/planetscale-rewind.webp)

When we covered Prisma above, we mentioned there are 3 pillars constituting a full-stack application:

1. The code (stateless part).
1. The data (stateful part).
1. And how the code interacts with the data.

For the data part, MongoDB is a popular choice, people choose it because of its usability rather than ubiquity. For hosting mission-critical application data such as user info, customer order, and billing, you still want a SQL-based relational database. PlanetScale is based on MySQL, enhanced with Vitess scalability, and crafted for usability by the amazing PlanetScale product team. These properties make PlanetScale an attractive choice. It seems to combine the best of both worlds, retaining all the SQL database benefits while not sacrificing developer experience.

### Neon

Neon is another open source database just announced.

![_](/content/blog/database-as-code-landscape/neon-overview.webp)

At a high level, it shares a lot of similarities with PlanetScale, serverless, developer productivity, fully managed.

![_](/content/blog/database-as-code-landscape/neon-about.webp)

The major difference lies in the technology stack:

- Neon is on the PostgreSQL camp while PlanetScale is MySQL-based.
- PlanetScale leverages Vitess to offer its advanced database features, while Vitess itself is a middleware on top of the MySQL server node. Neon takes a more drastic approach to build a dedicated storage layer to offer those desired features.

Neon could have higher potential because it has better control over the entire stack. It would be very interesting to see how Neon progresses compared to PlanetScale.
The love-hate relationship between MySQL and PostgreSQL is never-ending, from vanilla MySQL vs PostgreSQL, distributed database TiDB vs CockroachDB, cloud database AWS Aurora vs GCP AlloyDB, and now to the developer-centric database PlanetScale vs Neon.

## The Misfits

### Dolt

![_](/content/blog/database-as-code-landscape/dolt-overview.webp)

Dolt is unique on its own. The website describes it as a database system with Git-like version control.

![_](/content/blog/database-as-code-landscape/dolt-about.webp)

Dolt is drastically different from other database systems because it builds an engine with built-in Git semantics. This is a double-edged sword, on one hand, it brings those desired Git properties, on the other hand, it imposes challenges of optimizing the typical OLTP workload.

Dolt takes a much bolder move to adopt Database as Code since it blurs the lines between database and code. It currently positions itself as bringing the Git semantics into the database. Would the other way around work as well or even better, bringing the database semantics into Git? After all, many applications have already used Git as the only data store.

## The Bytebase

![_](/content/blog/database-as-code-landscape/bytebase-overview.webp)

Bytebase is an open source project that started in Jan 2021. It also shares some traits with the aforementioned products:

- Like Liquibase / Flyway / Sqitch, Bytebase uses migration-based approach to apply database schema changes.
- Like Prisma, Bytebase offers a fully-fledged web UI to conduct database development activities (schema, data change, SQL query).
- Like Atlas, Bytebase employs a modern tech stack, using Go instead of Java.
- Like PlanetScale / Neon, Bytebase focuses on developer experience. One example is the VCS integration, Bytebase provides a point-and-click wizard to configure VCS (the similar experience you find in Vercel / Netlify to link the code repository):

![_](/content/blog/database-as-code-landscape/bytebase-vcs.webp)

Bytebase is a jack-of-all-trades and the master of team collaboration:

- A standalone developer team can host a Bytebase workspace to manage database development activities.
- A DBA or platform team can also host a Bytebase workspace to be used by all the product teams in the entire organization.
- It has native VCS integration to streamline the code and database development together.
  Bytebase has concepts Project, Issue because it resembles systems like Jira, GitLab / GitHub.

![_](/content/blog/database-as-code-landscape/bytebase-issue-detail.webp)

It also has concepts `Tenant`, `Environment` to manage database changes for multi-tenant applications spanning multiple environments.

![_](/content/blog/database-as-code-landscape/bytebase-tenant.webp)

Bytebase also provides built-in schema review policies to enforce the schema standard across the whole engineering organization.

![_](/content/blog/database-as-code-landscape/bytebase-schema-review.webp)

Bytebase is envisioned to be the counterpart of GitLab / GitHub to manage the database development aspect. It's positioned as a Database DevSecOps solution for team collaboration.

![_](/content/blog/database-as-code-landscape/bytebase-position.webp)

How Bytebase compares against other tools:

|           | Language        | Change Format           | Genre                         | Interface | VCS Integration | Collaboration | Multi-tenancy |
| --------- | --------------- | ----------------------- | ----------------------------- | --------- | --------------- | ------------- | ------------- |
| Liquibase | Java            | XML / YAML / JSON / SQL | Migration-based               | CLI       |
| Flyway    | Java            | SQL                     | Migration-based               | CLI       |
| Sqitch    | Perl            | SQL                     | Migration-based               | CLI       |
| Atlas     | Go              | Custom DSL              | State-based & Migration-based | CLI       |
| Prisma    | TypeScript      | Custom DSL              | State-based                   | CLI + UI  | ✅              | ✅            |
| Bytebase  | Go + TypeScript | SQL                     | Migration-based\*             | CLI + UI  | ✅              | ✅            | ✅            |

_\*Though Bytebase uses migration-based approach, it records schema snapshot before and after the migration. Thus it also retains some state-based benefits such as drift detection_

## The Summaries

Though the idea of Database as Code is not new, the trend and innovation have been much accelerated in the last 2 years:

- Commercial companies like GitLab, GitHub keep investing heavily in the Git-based DevOps infrastructure.
- Commercial companies like HashiCorp leverages the Git infrastructure and build innovative products like Terraform. The success of Terraform in turn popularizes the GitOps workflow and transforms the industry mindset from point-and-click systems into code-based systems.
- The proliferation of open source ecosystem. Coincidentally, all products in this space are either open source projects or their derivations.

![_](/content/blog/database-as-code-landscape/star-history.webp)

- New building primitives were invented to challenge the status quo:
  - The invention of the V8 JavaScript Engine and Node.js opens the door for frontend engineers to interact with the databases directly. The flock of frontend engineers demands a high bar for developer experience.
  - Thanks to its pragmatic design and riding the wave of cloud computing, Go becomes a mainstream language and challenges the common wisdom of using Java to build backend applications. Especially in the cloud-native era, Go even dominates the market. For deploying a Java-based program, you need to install JVM first, which is not needed for Go. Just by adopting Go, tools like Bytebase and Atlas gain a competitive edge against Liquibase / Flyway. Not to mention the developer productivity boost offered by the language itself.
- Even though the database market is very mature, however, the market is too lucrative to ignore. Becoming the next Snowflake is every database practitioner's wide dream. New database systems were built and the bar has been raised higher and higher. Core database capability and performance are just table stakes, to differentiate, they have to compete for developer experience.

The iconic [Evolutionary Database Design](https://www.martinfowler.com/articles/evodb.html) was written in 2016. Though the phrase "Database as Code" was not coined there, that article summarized the accumulated wisdom of applying Database as Code practice in the decade before.

![_](/content/blog/database-as-code-landscape/you-do-not-need-army-of-dba.webp)

The article also predicted a trend that a sizable DBA team will become less common. Nowadays, many serious engineering teams still need DBA's expertise, meanwhile, interacting with databases has also become developers' daily routine.

The power dynamics for managing database development have shifted over time, and the quest for better developer experience and efficient developer workflow is more demanding than ever.

It requires a delicate dance among the database systems, the database tools, and the industry mindset to conquer it. Database as Code is the critical puzzle and the timing couldn't be better to build in this space.

![_](/content/blog/database-as-code-landscape/bytebase-land.webp)



A few days ago, we posted a question on HN: [Ask HN: Is DBA still a good job?](https://news.ycombinator.com/item?id=31309729) The question quickly drew the attention of the HN community and got 236 thought-provoking comments. We share and feel the challenges, the frustration, the fatigue and the expectation.

We want to preserve all these heated discussions and help more people develop a multi-dimensional perspective on DBAs. That's how an idea for a blog series emerges -- **D·D·D** (DBA, Database, and Developer).

As the debut of this series, we compiled 10 stories about DBAs based on the replies and comments from the [HN thread](https://news.ycombinator.com/item?id=31309729): we adopted the Decameron style, made up the story background, and borrowed the true stories shared by the commenters and turned them over to the storytellers (all credits go to the rightful owners). Some of these storytellers had experience as full-time DBAs; the others may be developers who have worked with DBAs before. You can regard this article as the appetizer of a full course meal. The crew welcomes all kinds of feedback and, last but not least: Bon Appetite!

10 people, consisting of developers and DBAs from different companies, woke up in a locked-up room. Apart from basic furniture, the room seems as normal as it could be except for a wooden board hung above the door with 3 letters carved on it -- DDD.

Nobody knows what happened and how they ended up there. Just when they were about to smash the windows, an electronic screen flashed for a few seconds and displayed their way out:

_"One true story about DBAs per day, you'll only get locked up for 10 days."_

Somebody sneered at the somehow sentient screen:

"Stupid rule...What could possibly happen if we don't?"

Another sentence appeared on the screen:

_"You could leave, but your team's databases will be dropped and won't be recovered."_

Dead silence permeats the room. After a while, somebody finally breaks the ice:

"Well, I'll go first."

## Day 1 From [donatj](https://news.ycombinator.com/user?id=donatj): Honestly Wish We had a DBA

We had a DBA about 6 years ago, he was one of the smartest guys I've ever worked with, and knew his stuff inside and out. I would recommend a DBA highly to anyone having growth issues. I honestly don't think we would have scaled without him. I learned a ton from him.

He got let go for basically having a really bad temper, and we decided not to look for a new DBA. I was sad he was gone but also glad to not be getting screamed at. It feels silly, but I've got really unresolved and mixed feelings about the whole thing. I genuinely really liked the guy, loved talking music and movies with him, but he would heel turn in an instant and just ruin your day.

Honestly wish we had a DBA, I ended up picking up a lot of his responsibilities. I'd love to have someone I could learn from. Basically, I'm getting real sick of optimizing reports.

The screen really is sentient, even intelligent at some level. It automatically summarized the story:

_"Honestly wish we had a DBA"_

## Day 2 From [steve_adams_86](https://news.ycombinator.com/user?id=steve_adams_86): Both Brilliant, both jerks

This is strange and funny to read; the only two DBAs I've worked with matched this description perfectly.

The first guy was so irate and literally yelling about his entitlement to punish us for making bad architectural decisions that I thought he was joking. I just laughed, but he got angrier. Then it clicked after maybe five or ten seconds – he was in the process of verbally punishing us for querying the database too much.

The second guy was similar, but didn't yell. Still super protective of his domain, almost antagonistic about us integrating with the database at all.

Both brilliant, taught me more than I can recount here, hilarious and interesting… But total jerks too, and both let go more or less for that reason.

One they had a great system in place and the product felt mature, the companies axed them.

The screen flashes:

_"All brilliant, all jerks."_

DBAs in the room frowned a little.

## Day 3 From [jamal-kumar](https://news.ycombinator.com/user?id=jamal-kumar): Gone DBA

Is this the DBA gone off the rails story thread?

I tried to hire a guy for a postgres DBA at a company I had worked at. I knew him from before as a MS SQL DBA from a previous company and hoped he could fulfill the role, he said he could. The guy saved our asses in the previous case.

We gave him like a month paid time to get acquainted with postgres. Dude DISAPPEARS, gets his vpn keys revoked and everything because we're like what the hell. A month later he sends this big long email saying how he got in some altercation with the police, and landed in jail... it was just way too rambling to take seriously. We ask a mutual friend what the hell was up and he said that since he was working too much his wife CONFISCATED HIS CELL PHONE.

I think we called him 'ballgag \*\*\*' (fill in the blank with your least favorite person's name) after that

These guys are worth their weight in gold though, I think I heard he ended up getting a job at Microsoft down the line.

The screen switches to today's theme:

_"Gone DBA"_

## Day 4 From [Simon_O_Rourke](https://news.ycombinator.com/user?id=Simon_O_Rourke): He was Supposed to Know Everything

I had eerily similar experiences from an older DBA guy, who was going through college in his 40's while working away. He knew his stuff, helped a lot optimizing the ETL process, but could turn nasty in an instant, and had a major chip on his shoulder about younger analysts with college degrees.

Only thing, was this guy had zero programming experience outside SQL and Bash. Anytime he had a question in a meeting about some calling Java process, he used to wait until the meeting was finished and then grab five minutes with me privately to ask about whatever. So there was this perceived weakness that his professional persona "knew everything", which meant he couldn't ask fundamental questions or try to (publicly) learn things outside his domain.

In the end, we moved to Amazon Redshift, and he was progressively moved into a smaller and smaller role, where now he just curates 2-year old JIRA tickets. Probably knows he can't get a similarly well-paying gig elsewhere now.

The familiar flashes appeared once more:

_"He was supposed to 'know everything'"_

## Day 5 From [skc](https://news.ycombinator.com/user?id=skc): “UR RUINING MY F\*\*\*\*ING DATABASE”

This is eerily similar to my experiences with two very, very good DBAs I worked with.

I'm now wondering if there is something about the role that lends itself to such behavior. One day they are super pleasant, helpful and friendly. The next they are chewing people out for seemingly minor and random transgressions and saying things like "ruining my fucking database".

Today these guys remind me a lot of JK Simmons character in "Whiplash"

The screen displays an image this time:
![roaring-dba](/content/blog/_shared/roaring-dba.webp)

**The DBAs among these 10 people have been humble audiences for 5 days. This picture becomes the last straw to break their nerves. They decided to take the lead now.**

## Day 6 From [forinti](https://news.ycombinator.com/user?id=forinti): Try to be the person I needed help from before

I was a developer and turned into a DBA by necessity. When I was still just a dev, I couldn't get the support I needed from the DBAs, so now I try to be the person I needed help from before.

But, I now understand the problem. At my organisation we have only 2 DBAs, and we can't give all of our time to this task.

To be a DBA is an endless battle against the entropy some devs try to create. The data model should really always be validated by someone with more knowledge and experience. Also, some young devs come up with crazy ideas (for instance, we should not use foreign keys). Others want to load insane amounts of data to process in the database, instead of preprocessing, or using a staging database. There is a continuous stream of bad ideas being implemented.

And when a bad idea gets implemented, it is really hard to undo it and it tends to just create more chaos: you need materialised views to get around bad modelling, or weird views to compensate for duplicate data, etc.

So, yes, a DBA is a really important role. With regards to it being a good job, it depends if your company takes it seriously and puts you in the development process, otherwise you'll be in for a lot of stress.

Screen displays:

_"Try to be the person I needed help from before"_

## Day 7 From [compton93](https://news.ycombinator.com/user?id=compton93): For that company my role was priceless

I hate to imagine how many startups out there don't even create indexes and just consider it to be a database problem and increase CPU/RAM and look the other way.

I worked for several years at a semi-startup as a Database Engineer where my role was to guide developers in writing performant SQL (and writing indexes for them) and architect their schema to be inline with our future plans and various other database tasks (managing query plans, being an expert on the database feature set etc). I even created an internal course: SQL School, that I included the directors/customer support teams in.

To that specific company my role was priceless, new features could be built in 1/2 the time with an expert writing the queries and handling the database. My programmatic analysis of our 20 year old code base had 5000 unique queries and 3000 more when accounting for dynamic SQL. Not gonna lie it was a complete mess but if I didn't exist they would have needed a lot more database resources. It was a terrible code base and any plan to refactor and avoid this mess would still need my role to do the transition.

The screen flashes and shows:

_"For that company my role was priceless"_

## Day 8 From [Twisell](https://news.ycombinator.com/user?id=Twisell): Exhausting yet rewarding

I would argue that it's way more accurate to say this role is actually outsourced in most organizations with all the tradeoffs that come with that strategy. I begged my former employer to subscribe to a good PostgreSQL support company. Guess what the one we picked is constantly looking to hire new DBA to sustain growth...

I was in database engineering/administration position for the last 10 year on a small company. It was exhausting because management wouldn't care to rely one guy to manage the whole data stack. It was rewarding because the CEO saw me as probably smarter than I was because I knew SQL well enough to produce outstanding value as a single individual.

I spent a few years complaining that my colleagues didn't know their database well enough, and it was causing unnecessary bugs and poor performance.

I wanted the company to pay for some basic courses on the databases we were using, especially for the more junior Devs.

Instead we switched database like 11 times and now I don't know the database either.

The bugs and poor performance lingers though.

The screen changed the sentence to:

_"Exhausting yet rewarding"_

## Day 9 From [jhugo](https://news.ycombinator.com/user?id=jhugo): Conflict comes from lack of understanding

I think this kind of conflict often comes from frustration at developers not having much understanding of the underlying technology that the network engineer / DBA is responsible for.

Networks & DBs present abstractions, but they're very leaky ones, yet developers often expect to just treat them as magical black boxes about which they don't need to know much of the inner workings, constraints, tradeoffs etc. That makes the interface between the network engineer or DBA and software developers a natural site of conflict.

(You even see this above in this very thread, someone complaining that a DBA was punishing developers for "querying the database too much". Most likely the DBA was actually upset about how they were querying the database, not that they were querying it too much, but the developers want it to "just work" so the distinction isn't important to them.)

Screen flashes:

_"Conflict comes from lack of understanding"_

## Day 10 From [niklasrde](https://news.ycombinator.com/user?id=niklasrde) &[ datalopers](https://news.ycombinator.com/user?id=datalopers): The lost art -- data modeling and SQL

Same at my previous role - we did have some people who were really good at some point, and into DBs. We had a very solid Redis and PostgreSQL set-up, and some advanced stuff for simple data in Redis - but once that knowledge fades with attrition, making space for continued personal development into how two very different DBMS work for a small team is not easy, and it just stays untouched, disliked, and somewhat abandoned forever more.

I honestly think the thing that costs most companies the most in their hosting is developers not using databases correctly

100%. Data modeling and SQL has become a lost art.

The screen flashes and literally drops a few pixel tears:

_"The lost art -- data modeling and SQL"_

## Finale

While the last story approaches its end, the doors and windows open up widely. 10 people storm out, rush back to their office, and thoroughly check their database. Everything is fine, nothing deleted. They sigh with relief and start to delve into their daily work, as concentrated as ever.

It all starts with one sentence:

**"Is DBA still a good job?"**

We look forward to your story.


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