Database migrations are fundamental to modern software development, allowing teams to evolve their database schema in a controlled and versioned manner. As applications grow and requirements change, the ability to reliably alter your database is crucial for maintaining data integrity and application stability.

Atlas was originally created to support Ent, a popular Go ORM. From the start, Ent shipped with a simple "auto-migration" feature that could set up the database schema based on the Ent schema. However, as the project grew popular, it became clear that a more robust versioned migration system was needed.

Ent's authors had hoped to add functionality based on the existing "auto-migration" engine to generate migration files, and use an off-the-shelf migration tool to apply them. The most promising candidate was golang-migrate, a widely adopted migration tool in the Go community renowned for its simplicity and wide database support. But like many tools that start simple and grow popular, we realized that golang-migrate, too, has its limitations, and they led us to expand on its abilities.

In this article, we’ll explore some common challenges teams face with traditional migration tools like golang-migrate, and how Atlas takes a different approach to improve the developer experience.

Prepared for SREDay London 2025

Introduction​

Platform engineering is rapidly emerging as a discipline aimed at reducing cognitive load for developers, enabling self-service infrastructure, and establishing best practices for building and operating software at scale. While much of the conversation focuses on CI/CD, Kubernetes, and internal developer platforms, one crucial aspect often remains overlooked: database schema management.

Despite being at the heart of nearly every application, schema changes are still a major source of friction, outages, and bottlenecks. In this post, we'll explore why database schema management deserves a dedicated chapter in the platform engineering playbook and how organizations can integrate it into their platform strategies.

The prompt that nuked the database​

Let me tell you a not-so-fictional story about a developer named Alice. Alice is a backend engineer at a fast-growing startup. One day, her manager asked her to make a small change to the database. The data engineering team was complaining that they were seeing duplicate emails in the user table, and they suspected that the email column did not have a unique constraint.

Hey everyone!

It's been a few weeks since our last release, and we're excited to share today everything that's new in Atlas v0.32. This release is packed with new features, improvements and bug fixes that will make your experience with Atlas even better.

Here are the highlights of this release:

• Ask AI - Since its modest beginning, Atlas has come a long way. What started as a simple CLI tool for declarative schema management is now a full-blown platform. We know that the learning curve for new users can be steep, which is why we are introducing new AI-powered features to help you get started with Atlas.
• SQL Importing - As projects grow, teams often want to split their schema definition across multiple files. Because SQL definitions are imperative and rely on the order of statements, splitting them can be challenging. With the new importing feature its easy to break large SQL schema definitions into smaller parts while keeping them correct and ordered.
• Improved Ent Loader - Users of the popular Ent ORM can use the ent:// URL scheme to load their schema into Atlas. We have added support for multi-schema migrations, composite schemas, and Ent's globalid feature.
• SQL Server Improvements - We have made several improvements to the SQL Server support in Atlas, including support for Full Text Search Index and Temporal Tables.
• PostgreSQL Improvements - We have added support for defining Foreign Servers and Unlogged Tables in PostgreSQL.

Automatic ER Diagrams and Docs for ClickHouse​

When working with a relational database like ClickHouse, understanding the database schema becomes essential for many functions in the organization. Who cares about the schema? Almost everyone who interacts with your data:

• Software engineers and architects use knowledge about the schema to make design decisions when building software.
• Data engineers need to have an accurate understanding of schemas to build correct and efficient data pipelines.
• Data analysts rely on familiarity with the schema to write accurate queries and derive meaningful insights.
• DevOps, SREs, and Production Engineers use schema information (especially recent changes to it) to triage database-related production issues.

Having clear, centralized documentation of your database's schema and its changes can be a valuable asset to foster efficient work and collaboration. Knowing this, many teams have developed some form of strategy to provide this kind of documentation:

• Diagramming tools. Teams use generic diagramming tools like Miro or Draw.io to maintain ER (Entity-Relation) Diagrams representing their database schema. While this is easy to set up, it requires manually updating the documents whenever something changes, often causing documents to go stale and become obsolete.
• Data modeling tools. Alternatively, teams use database modeling software like DataGrip or DBeaver. While these tools automatically inspect your database, understand its schema, and provide interactive diagrams, they have two main downsides: 1) Since they run locally, they require a direct connection and credentials introducing a potential security risk; 2) They do not enable any collaboration, discussion, or sharing of information.
• Enterprise Data Catalogs like Atlan or Alation, provide extensive schema documentation and monitoring; however, they can be quite pricey and difficult to set up.

Enter: Atlas Schema Monitoring​

Atlas offers an automated, secure, and cost-effective solution for monitoring and documenting your ClickHouse schema.

With Atlas, you can:

• Generate ER Diagrams: Visualize your database schema with up-to-date, easy-to-read diagrams.
• Create Searchable Code Docs: Enable your team to quickly find schema details and usage examples.
• Track Schema Changes: Keep a detailed changelog to understand what's changed and why.
• Receive Alerts: Get notified about unexpected or breaking changes to your schema.

All without granting everyone on your team direct access to your production database.

Python has been a top programming language for the past decade, known for its simplicity and rich ecosystem. Many companies use it to build web apps and server software, thanks to frameworks like Django and SQLAlchemy.

One of the most common (and often loathed) tasks when building backend applications is managing the database schema. As the app's data model evolves, developers need to modify the database schema to reflect those changes. This is where database schema migration tools come into play.

Hey everyone!

Welcome to the second Atlas release of 2025, v0.31! We're excited to share the latest updates and improvements with you. In this release you will find:

• Custom schema rules: You can now define custom rules for your database schema and have Atlas enforce them for you during CI.

• pgvector support: We've added support for managing schemas for projects that use the LLM-based pgvector extension.

• Drift detection: It is now simpler to set up drift detection checks to alert you when a target database isn't in the state it's supposed to be in.

• Multi-project ER Diagrams: you can now create composite ER diagrams that stitch schema objects from multiple Atlas projects.

Happy new year everyone, and welcome to our first release of 2025, Atlas v0.30! We have some exciting new features and improvements to share with you.

In this release you will find:

1. Simplified Schema Monitoring: Previously you needed to install a long-running agent on your database VPC to monitor your schema. Schema monitoring is now even simpler with the introduction of a new agentless monitoring mode.
2. Drizzle Support: We now support Drizzle, a popular ORM for Node.js. You can now use Atlas to automate schema migrations for your Drizzle projects.
3. Bitbucket Pipelines: We have added support for Bitbucket Pipelines, making it easier to integrate Atlas into your Bitbucket CI/CD workflows.
4. Custom Kubernetes Configurations: Atlas Pro users can now provide custom atlas.hcl configurations for their Kubernetes Custom Resource Definitions (CRDs) using the Atlas Operator.
5. txtar Editor Support: The Atlas JetBrains plugin now supports editing txtar files, used by the Atlas CLI to define pre-migration checks but also useful for other purposes.

Today we are happy to announce that Atlas has achieved SOC2 compliance for the third year in a row. This is an important milestone for us, demonstrating our commitment to providing a solid infrastructure for our users and customers.

As a company that is trusted by its customers to handle mission-critical databases, we are committed to ensuring the highest standards of security, availability, and confidentiality. Achieving SOC 2 compliance demonstrates our dedication to safeguarding customer data, maintaining trust, and adhering to industry best practices.

"Month over month, we see smaller and smaller incidents.", Luiz Casali, Sr Engineering Manager

Company Background​

Unico is a leading digital identity technology provider in Brazil, developing secure and efficient digital identity solutions for businesses and individuals. Their platform helps organizations streamline identity verification processes, delivering a seamless user experience while enhancing security and reducing fraud.

The Missing Layer: Tackling Complexity, Outages, and Risks in Database Schema Management​

At Unico, the Platform Engineering team, led by Luiz Casali, is focused on improving developer productivity. "Reducing complexity for developers is one of our top priorities," Luiz explained.

Unico's Platform team had previously built solutions to automate CI/CD workflows for code using Bazel and GitHub Actions and for infrastructure using Terraform and Atlantis. The team was missing a standardized solution for managing database schema changes.

This gap introduced several pressing issues:

1. Risky Manual Processes: Database schema changes (migrations) were performed manually, increasing the chance of human error.
2. Unreliable Deployments: Unplanned, database-related outages were common, emphasizing the need for a safer way to handle database changes.
3. Compliance Requirements: The team needed to document and review schema changes to maintain governance standards, but the lack of automation made this challenging.

Determined to bridge this gap and establish a safer, more efficient solution for developers, Unico's Platform Engineering team began researching the best database migration tools. Thiago da Silva Conceição, a Site Reliability Engineer (SRE) in the team, took the lead on this technical evaluation.

Hey everyone!

We are excited to announce the release of Atlas v0.29, which continues our journey to make working with database easier, safer and more reliable. This release includes several significant updates that we are happy to share with you:

• Approval flows for the Kubernetes Operator: Moving to a declarative way of managing database schemas has plenty of advantages, but many teams want to see and approve changes before they are applied. Doing this from the CLI is straightforward, but until recently it was not easy to provide this experience in Kubernetes-based workflows.

  With the new approval flows, you can now review and approve schema migrations seamlessly, ensuring database changes are well-governed while maintaining deployment velocity.

• Prisma support: Following our integrations with some of the most popular ORMs in our industry, we are happy to announce our official guide on using Atlas to manage database schemas for Prisma projects.

• GitLab CI/CD Components: Integrating GitLab CI with Atlas just got much easier with the new GitLab CI/CD components.

• IntelliJ Plugin: Our IntelliJ plugin has been upgraded with code folding, inline SQL syntax highlighting and suggestions, and syntax highlighting within heredoc clauses.

• Timeseries Engine support for ClickHouse: ClickHouse users can now explore beta support for timeseries data in Atlas.

• Constraint Triggers support for PostgreSQL: PostgreSQL users can now manage constraint triggers with Atlas.