Deterministic migration engine for AI agents

manage your database schema as code with atlas

GitOps-native CI/CD for secure and compliant database management

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Goodbye manual schema migrations, Hello Atlas

Modern schema migration workflows that scale with confidence

The Old Way

The Atlas Way

The Old Way

manual schema changes in prod

schema scattered across a million scripts

schema drift between local, dev and prod

The Atlas Way

a/schema.sql

@@ -3, 6 +3,7 @@

11CREATE TABLE 'categories' (

22 'category_name' varchar(255) NOT NULL,

33 'category_description' text NULL,

5+'long_desc' TEXT NOT NULL,

66 'updated_at' timestamp NULL ON UPDATE CURRENT_TIMESTAMP,

77 'created_at' timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,

88 PRIMARY KEY ('id').

99(END)

Change Code

atlas git:(main) x atlas schema apply --env localPlanning migration statements (1 in total):-- modify "categories" table:- > ALTER TABLE "categories" ADD COLUMN "long_desc" text NOT NULL;

Analyzing planned statements (1 in total):-- no diagnostics found

Automatically Plan and Apply

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ORMs

See Comparison

Codebase

Define your database schema as code

Atlas understands your database schema in any language

SQL

Atlas HCL

Python

Node.js

Java

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C#

PHP

schema.sql

CREATE TABLE users (
  id serial NOT NULL,
  name varchar(255) NOT NULL,
  email varchar(255) UNIQUE NOT NULL,
  PRIMARY KEY (id)
);

CREATE TABLE user_logs (
  id serial NOT NULL,
  user_id int NOT NULL,
  body text NOT NULL,
  PRIMARY KEY (id),
  CONSTRAINT user_fk FOREIGN KEY (user_id) REFERENCES users(id)
);

Support

Works with the industry's best databases

Manage your database schema as code with Atlas

Migration

Automatic migration planning

Atlas calculates the diff and plans safe migrations for you

Declarative Workflow

Versioned Workflow

$ atlas schema apply

Planning migration statements (1 in total):

  -- create "users" table:
    -> CREATE TABLE "public"."users" (
         "id" serial NOT NULL,
         "name" character varying(255) NOT NULL,
         "email" character varying(255) NOT NULL,
         PRIMARY KEY ("id"),
         CONSTRAINT "users_email_key" UNIQUE ("email")
       );

-------------------------------------------

Analyzing planned statements (1 in total):

  -- no diagnostics found

  -------------------------
  -- 22.793167ms
  -- 1 schema change

-------------------------------------------

Applying approved migration (1 statement in total):

  -- create "users" table
    -> CREATE TABLE "public"."users" (
         "id" serial NOT NULL,
         "name" character varying(255) NOT NULL,
         "email" character varying(255) NOT NULL,
         PRIMARY KEY ("id"),
         CONSTRAINT "users_email_key" UNIQUE ("email")
       );
  -- ok (14.210916ms)

  -------------------------
  -- 14.304291ms
  -- 1 migration
  -- 1 sql statement

“Atlas enables our team to efficiently and safely manage our application schema. With features like linting, automated migrations for our ORM, and Kubernetes support, it seamlessly integrates into our development ecosystem.”

Michael Caulley, Software Eng Lead

“Generating and applying migrations is very straight-forward. A powerful and elegant tool, we are now integrating Atlas into our GitHub workflows. Atlas is a natural extension of the tools we already use and a joy to work with!”

Noreen Wu, Senior Software Engineer

“Finally, a tool that eases the headaches of dealing with migrations, dirty states, merging conflicts, and thinking about rolling back to previous states... hands down, with Atlas, I've had the best experience ever!”

Alexander Sadowski, Full Stack Developer

verification

Formal verification

Atlas verifies schema changes using a rigorous, deterministic policy engine

Code Review Agent

atlas migrate lint on dirs/ecommerce/migrations

CLI Tool

$ atlas migrate lint

Automate code review on

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Projects

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STATUS

STEP

RESULT

1 new migration file detected

20250410131547.sql

ERD and visual diff generated

View Visualization

Analyze 20250410131547.sql2 reports were found in analysis

Destructive changes detectedDropping non-virtual column "email_address"

Data dependent changes detectedAdding a non-nullable "varchar" column "email" on table "users" without a default value

Automate code review on

Deployment

Modern deployments

Deploy schema changes with confidence using our modern CI/CD pipeline

schema.tf

terraform {
  required_providers {
    atlas = {
      source  = "ariga/atlas"
      version = "~> 0.9.7"
    }
  }
}

provider "atlas" {
  dev_url = "docker://postgres/15/myapp"
}

data "atlas_schema" "sql" {
  src = "file://${path.module}/schema.sql"
}

resource "atlas_schema" "postgres" {
  url = "postgres://root:pass@localhost:5432/app?sslmode=disable"
  hcl = data.atlas_schema.sql.hcl
}

$ terraform apply

data.atlas_schema.sql: Reading...
data.atlas_schema.sql: Read complete after 2s [id=p93KLX2q4UI326LN/4cssQ]

Terraform will perform the following actions:

  # atlas_schema.postgres will be created
  + resource "atlas_schema" "postgres" {
      + hcl = <<-EOT
            table "users" {
              schema = schema.myapp
              column "id" {
                null = false
                type = int
              }
              column "name" {
                null = false
                type = varchar(255)
              }
              primary_key {
                columns = [column.id]
              }
            }
        EOT
      + id  = (known after apply)
      + url = (sensitive value)
    }

Plan: 1 to add, 0 to change, 0 to destroy.

The following SQL statements will be executed:

CREATE TABLE users (
  id SERIAL PRIMARY KEY,
  name VARCHAR(255) NOT NULL
);

Atlas Cloud

A DBRE platform for operating production databases

Built for modern enterprises with security guardrails, compliance controls, intelligent automation, and governance features that keep database operations safe, auditable, and compliant.

Source of Truth

Promote with Confidence

Trace Everything

Schema Statistics

Production Safeguards

A single, versioned source of truth for all database artifacts

Source of Truth

A single, versioned source of truth for all database artifacts

Promote with Confidence

Safely promote database changes from dev to prod with guardrails

Trace Everything

Audit every change - who changed what, where it ran, and how it behaved

Schema Statistics

Atlas continuously analyzes schema statistics to provide actionable feedback

Production Safeguards

Control who can deploy or rollback with environment-aware permissions

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Monitoring

Continuous Monitoring & Auto-Fix

Detects drifts in real time and automatically remediates unauthorized changes, keeping environments consistent without manual intervention. All automated fixes are fully reversible.

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atlas-copilot

Your DBA Copilot

AI-powered assistant for effortless database operations

Get started in minutes

Chat with Atlas Copilot to set up your project fast

Fix issues fast

Iterate with Atlas to quickly resolve to ensure reliable migrations

Generate tests

Use free language to generate unit tests for your schema and migrations

Govern schemas

Use Copilot to generate schema rules and predicates to govern schemas based on your guidelines

atlas-copilot

user@atlas~$ atlas copilot

Atlas

How can I help you today?

User

Help me fix my latest migration

Atlas

I see that your migration is adding a unique constraint on a column in postgres.To do this postgres needs to acquire an ACCESS EXCLUSIVE lock on the table.It's possible to achieve the same result without locking. Let me help!

Editing migration 20250410131547_add_uniq_email.sql

Built for Every Team, Every Workflow

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GitOps-native CI/CD for secure and compliant database management

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