How to migrate from Liquibase to Atlas?

Atlas provides tools to inspect existing databases and generate HCL or SQL schemas, but you'll need to manually convert Liquibase XML/YAML files or use the database inspection feature to bootstrap migrations. Start by running 'atlas schema inspect' on your production database.

Atlas vs Prisma Migrate: which is better for a TypeScript project?

Atlas offers more flexibility with dual workflows and supports multiple ORMs, while Prisma Migrate is tightly integrated with Prisma's ecosystem. Choose Atlas if you need cross-ORM support or declarative migrations; stick with Prisma Migrate for simpler, Prisma-only setups.

Can Atlas handle data migrations or only schema changes?

Yes, Atlas supports data management through declarative SQL inserts and seed data in schema files, but for complex data transformations, you may need to write custom migration scripts or use the versioned workflow with manual SQL.

How to rollback a failed migration in Atlas?

In versioned migrations, Atlas uses a history table to track applied migrations, but rollbacks require manual SQL or reverting changes via new migration files. The declarative workflow doesn't support automatic rollbacks, relying on re-applying the desired state instead.

What databases does Atlas not support that are commonly used?

Atlas supports many popular databases like PostgreSQL and MySQL, but it lacks support for some niche or older systems like IBM DB2, Sybase, or Firebird. Always check the official list before adoption.

How to integrate Atlas with an existing Django migration history?

Atlas can load Django models via its ORM loader, but you'll need to reconcile existing migration files by inspecting the database state and generating new Atlas migrations, potentially requiring a one-time migration effort.

Atlas — Database Schema Migration Tool

What is Atlas?

Atlas is a language-agnostic tool for managing and migrating database schemas using modern DevOps principles. It offers both declarative (similar to Terraform) and versioned migration workflows, allowing teams to define their desired database state as code and automatically generate safe migration plans. It solves the problem of manual, error-prone database schema changes by bringing automation, safety, and collaboration to database management.

Target Audience

Development and DevOps teams working with relational databases who need to manage schema changes safely and collaboratively, especially those adopting infrastructure-as-code practices or using multiple ORMs across different programming languages.

Value Proposition

Developers choose Atlas for its unique combination of declarative and versioned migration workflows, extensive ORM support, built-in safety analyzers, and deep cloud-native integrations. Unlike traditional migration tools, Atlas automatically plans safe migrations and provides enterprise-grade features like drift detection, security-as-code, and a testing framework out of the box.

Declarative schema migrations with schema-as-code workflows

Use Cases

Best For

Teams adopting infrastructure-as-code practices for database management
Projects using multiple ORMs across different programming languages
Implementing safe, automated database migrations in CI/CD pipelines
Managing database security policies (roles, permissions, RLS) as code
Detecting and remediating schema drift in production databases
Unit testing database logic like functions, views, and triggers

Not Ideal For

Teams using a single, well-supported ORM with robust built-in migration tools (e.g., Django ORM or Prisma)
Projects with infrequent, simple schema changes that don't justify the overhead of a full DevOps toolchain
Environments requiring extensive third-party plugins or integrations not yet covered by Atlas's ecosystem
Legacy systems relying on unsupported databases or proprietary migration scripts

Pros & Cons

Pros

Dual Migration Workflows

Atlas supports both declarative (Terraform-like) and versioned migrations, allowing teams to choose or mix approaches based on project needs, as described in the README's key features.

Broad ORM Compatibility

With loaders for 16 ORMs across 6 languages, Atlas can generate migrations directly from existing code models, reducing manual SQL work and supporting polyglot teams.

Safety-First Linting

Includes over 50 built-in analyzers to detect destructive changes, data-dependent risks, and database-specific issues before production, enhancing migration safety.

Cloud-Native Integration

Offers deep integrations with Kubernetes, Terraform, GitHub Actions, and cloud IAM, enabling seamless automation in modern DevOps pipelines, as highlighted in the integrations section.

Security and Data Management

Allows managing roles, permissions, row-level security, and seed data as version-controlled code, promoting better security practices and auditability.

Cons

Complex Initial Setup

Requires configuring dev database URLs and understanding dual workflows, which can be overwhelming for teams new to schema-as-code, adding setup time and complexity.

Limited Ecosystem Maturity

Compared to established tools like Flyway or Liquibase, Atlas has fewer community-contributed plugins or extensions, which might limit customization for niche use cases.

Potential Breaking Changes

As a newer project with a supported version policy focusing on recent releases, Atlas may introduce breaking changes that could disrupt existing workflows, requiring careful upgrade planning.

Dependency on Atlas Syntax

Heavy use of Atlas-specific HCL for advanced features like testing and security-as-code can create vendor lock-in, making it harder to switch tools later.

Frequently Asked Questions

What is Atlas?

Target Audience

Value Proposition

Use Cases

Best For

Teams adopting infrastructure-as-code practices for database management
Projects using multiple ORMs across different programming languages
Implementing safe, automated database migrations in CI/CD pipelines
Managing database security policies (roles, permissions, RLS) as code
Detecting and remediating schema drift in production databases
Unit testing database logic like functions, views, and triggers

Not Ideal For

Teams using a single, well-supported ORM with robust built-in migration tools (e.g., Django ORM or Prisma)
Projects with infrequent, simple schema changes that don't justify the overhead of a full DevOps toolchain
Environments requiring extensive third-party plugins or integrations not yet covered by Atlas's ecosystem
Legacy systems relying on unsupported databases or proprietary migration scripts

Pros & Cons

Pros

Dual Migration Workflows

Atlas supports both declarative (Terraform-like) and versioned migrations, allowing teams to choose or mix approaches based on project needs, as described in the README's key features.

Broad ORM Compatibility

With loaders for 16 ORMs across 6 languages, Atlas can generate migrations directly from existing code models, reducing manual SQL work and supporting polyglot teams.

Safety-First Linting

Includes over 50 built-in analyzers to detect destructive changes, data-dependent risks, and database-specific issues before production, enhancing migration safety.

Cloud-Native Integration

Offers deep integrations with Kubernetes, Terraform, GitHub Actions, and cloud IAM, enabling seamless automation in modern DevOps pipelines, as highlighted in the integrations section.

Security and Data Management

Allows managing roles, permissions, row-level security, and seed data as version-controlled code, promoting better security practices and auditability.

Cons

Complex Initial Setup

Requires configuring dev database URLs and understanding dual workflows, which can be overwhelming for teams new to schema-as-code, adding setup time and complexity.

Limited Ecosystem Maturity

Compared to established tools like Flyway or Liquibase, Atlas has fewer community-contributed plugins or extensions, which might limit customization for niche use cases.

Potential Breaking Changes

As a newer project with a supported version policy focusing on recent releases, Atlas may introduce breaking changes that could disrupt existing workflows, requiring careful upgrade planning.

Dependency on Atlas Syntax

Heavy use of Atlas-specific HCL for advanced features like testing and security-as-code can create vendor lock-in, making it harder to switch tools later.

Frequently Asked Questions

Atlas

What is Atlas?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?

Atlas

What is Atlas?

Overview

Use Cases

Best For

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions

Related Projects

Found a gem we're missing?