Skip to main content
Kodelyth ECC
Skill

database-migrations

Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).

Invoke via:use database-migrations
Origin:ECC

Database Migration Patterns

Safe, reversible database schema changes for production systems.

When to Activate

  • Creating or altering database tables
  • Adding/removing columns or indexes
  • Running data migrations (backfill, transform)
  • Planning zero-downtime schema changes
  • Setting up migration tooling for a new project

Core Principles

  • Every change is a migration — never alter production databases manually
  • Migrations are forward-only in production — rollbacks use new forward migrations
  • Schema and data migrations are separate — never mix DDL and DML in one migration
  • Test migrations against production-sized data — a migration that works on 100 rows may lock on 10M
  • Migrations are immutable once deployed — never edit a migration that has run in production

Migration Safety Checklist

Before applying any migration:

  • [ ] Migration has both UP and DOWN (or is explicitly marked irreversible)
  • [ ] No full table locks on large tables (use concurrent operations)
  • [ ] New columns have defaults or are nullable (never add NOT NULL without default)
  • [ ] Indexes created concurrently (not inline with CREATE TABLE for existing tables)
  • [ ] Data backfill is a separate migration from schema change
  • [ ] Tested against a copy of production data
  • [ ] Rollback plan documented

PostgreSQL Patterns

Adding a Column Safely

-- GOOD: Nullable column, no lock
ALTER TABLE users ADD COLUMN avatar_url TEXT;
-- GOOD: Column with default (Postgres 11+ is instant, no rewrite)
ALTER TABLE users ADD COLUMN is_active BOOLEAN NOT NULL DEFAULT true;
-- BAD: NOT NULL without default on existing table (requires full rewrite)
ALTER TABLE users ADD COLUMN role TEXT NOT NULL;
-- This locks the table and rewrites every row

Adding an Index Without Downtime

-- BAD: Blocks writes on large tables
CREATE INDEX idx_users_email ON users (email);
-- GOOD: Non-blocking, allows concurrent writes
CREATE INDEX CONCURRENTLY idx_users_email ON users (email);
-- Note: CONCURRENTLY cannot run inside a transaction block
-- Most migration tools need special handling for this

Renaming a Column (Zero-Downtime)

Never rename directly in production. Use the expand-contract pattern:

-- Step 1: Add new column (migration 001)
ALTER TABLE users ADD COLUMN display_name TEXT;
-- Step 2: Backfill data (migration 002, data migration)
UPDATE users SET display_name = username WHERE display_name IS NULL;
-- Step 3: Update application code to read/write both columns
-- Deploy application changes
-- Step 4: Stop writing to old column, drop it (migration 003)
ALTER TABLE users DROP COLUMN username;

Removing a Column Safely

-- Step 1: Remove all application references to the column
-- Step 2: Deploy application without the column reference
-- Step 3: Drop column in next migration
ALTER TABLE orders DROP COLUMN legacy_status;
-- For Django: use SeparateDatabaseAndState to remove from model
-- without generating DROP COLUMN (then drop in next migration)

Large Data Migrations

-- BAD: Updates all rows in one transaction (locks table)
UPDATE users SET normalized_email = LOWER(email);
-- GOOD: Batch update with progress
DO $$
DECLARE
  batch_size INT := 10000;
  rows_updated INT;
BEGIN
  LOOP
    UPDATE users
    SET normalized_email = LOWER(email)
    WHERE id IN (
      SELECT id FROM users
      WHERE normalized_email IS NULL
      LIMIT batch_size
      FOR UPDATE SKIP LOCKED
    );
    GET DIAGNOSTICS rows_updated = ROW_COUNT;
    RAISE NOTICE 'Updated % rows', rows_updated;
    EXIT WHEN rows_updated = 0;
    COMMIT;
  END LOOP;
END $$;

Prisma (TypeScript/Node.js)

Workflow

# Create migration from schema changes
npx prisma migrate dev --name add_user_avatar
Apply pending migrations in production

npx prisma migrate deploy
Reset database (dev only)

npx prisma migrate reset
Generate client after schema changes

npx prisma generate

Schema Example

model User {
  id        String   @id @default(cuid())
  email     String   @unique
  name      String?
  avatarUrl String?  @map("avatar_url")
  createdAt DateTime @default(now()) @map("created_at")
  updatedAt DateTime @updatedAt @map("updated_at")
  orders    Order[]
  @@map("users")
  @@index([email])
}

Custom SQL Migration

For operations Prisma cannot express (concurrent indexes, data backfills):

# Create empty migration, then edit the SQL manually
npx prisma migrate dev --create-only --name add_email_index


-- migrations/20240115_add_email_index/migration.sql
-- Prisma cannot generate CONCURRENTLY, so we write it manually
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_users_email ON users (email);

Drizzle (TypeScript/Node.js)

Workflow

# Generate migration from schema changes
npx drizzle-kit generate
Apply migrations

npx drizzle-kit migrate
Push schema directly (dev only, no migration file)

npx drizzle-kit push

Schema Example

import { pgTable, text, timestamp, uuid, boolean } from "drizzle-orm/pg-core";
export const users = pgTable("users", {
  id: uuid("id").primaryKey().defaultRandom(),
  email: text("email").notNull().unique(),
  name: text("name"),
  isActive: boolean("is_active").notNull().default(true),
  createdAt: timestamp("created_at").notNull().defaultNow(),
  updatedAt: timestamp("updated_at").notNull().defaultNow(),
});

Kysely (TypeScript/Node.js)

Workflow (kysely-ctl)

# Initialize config file (kysely.config.ts)
kysely init
Create a new migration file

kysely migrate make add_user_avatar
Apply all pending migrations

kysely migrate latest
Rollback last migration

kysely migrate down
Show migration status

kysely migrate list

Migration File

// migrations/2024_01_15_001_create_user_profile.ts
import { type Kysely, sql } from 'kysely'
// IMPORTANT: Always use Kysely<any>, not your typed DB interface.
// Migrations are frozen in time and must not depend on current schema types.
export async function up(db: Kysely<any>): Promise<void> {
  await db.schema
    .createTable('user_profile')
    .addColumn('id', 'serial', (col) => col.primaryKey())
    .addColumn('email', 'varchar(255)', (col) => col.notNull().unique())
    .addColumn('avatar_url', 'text')
    .addColumn('created_at', 'timestamp', (col) =>
      col.defaultTo(sqlnow()).notNull()
    )
    .execute()
  await db.schema
    .createIndex('idx_user_profile_avatar')
    .on('user_profile')
    .column('avatar_url')
    .execute()
}
export async function down(db: Kysely<any>): Promise<void> {
  await db.schema.dropTable('user_profile').execute()
}

Programmatic Migrator

import { Migrator, FileMigrationProvider } from 'kysely'
import { promises as fs } from 'fs'
import * as path from 'path'
// ESM only — CJS can use __dirname directly
import { fileURLToPath } from 'url'
const migrationFolder = path.join(
  path.dirname(fileURLToPath(import.meta.url)),
  './migrations',
)
// db is your Kysely<any> database instance
const migrator = new Migrator({
  db,
  provider: new FileMigrationProvider({
    fs,
    path,
    migrationFolder,
  }),
  // WARNING: Only enable in development. Disables timestamp-ordering
  // validation, which can cause schema drift between environments.
  // allowUnorderedMigrations: true,
})
const { error, results } = await migrator.migrateToLatest()
results?.forEach((it) => {
  if (it.status === 'Success') {
    console.log(migration "${it.migrationName}" executed successfully)
  } else if (it.status === 'Error') {
    console.error(failed to execute migration "${it.migrationName}")
  }
})
if (error) {
  console.error('migration failed', error)
  process.exit(1)
}

Django (Python)

Workflow

# Generate migration from model changes
python manage.py makemigrations
Apply migrations

python manage.py migrate
Show migration status

python manage.py showmigrations
Generate empty migration for custom SQL

python manage.py makemigrations --empty app_name -n description

Data Migration

from django.db import migrations
def backfill_display_names(apps, schema_editor):
    User = apps.get_model("accounts", "User")
    batch_size = 5000
    users = User.objects.filter(display_name="")
    while users.exists():
        batch = list(users[:batch_size])
        for user in batch:
            user.display_name = user.username
        User.objects.bulk_update(batch, ["display_name"], batch_size=batch_size)
def reverse_backfill(apps, schema_editor):
    pass  # Data migration, no reverse needed
class Migration(migrations.Migration):
    dependencies = [("accounts", "0015_add_display_name")]
    operations = [
        migrations.RunPython(backfill_display_names, reverse_backfill),
    ]

SeparateDatabaseAndState

Remove a column from the Django model without dropping it from the database immediately:

class Migration(migrations.Migration):
    operations = [
        migrations.SeparateDatabaseAndState(
            state_operations=[
                migrations.RemoveField(model_name="user", name="legacy_field"),
            ],
            database_operations=[],  # Don't touch the DB yet
        ),
    ]

golang-migrate (Go)

Workflow

# Create migration pair
migrate create -ext sql -dir migrations -seq add_user_avatar
Apply all pending migrations

migrate -path migrations -database "$DATABASE_URL" up
Rollback last migration

migrate -path migrations -database "$DATABASE_URL" down 1
Force version (fix dirty state)

migrate -path migrations -database "$DATABASE_URL" force VERSION

Migration Files

-- migrations/000003_add_user_avatar.up.sql
ALTER TABLE users ADD COLUMN avatar_url TEXT;
CREATE INDEX CONCURRENTLY idx_users_avatar ON users (avatar_url) WHERE avatar_url IS NOT NULL;
-- migrations/000003_add_user_avatar.down.sql
DROP INDEX IF EXISTS idx_users_avatar;
ALTER TABLE users DROP COLUMN IF EXISTS avatar_url;

Zero-Downtime Migration Strategy

For critical production changes, follow the expand-contract pattern:

Phase 1: EXPAND
  - Add new column/table (nullable or with default)
  - Deploy: app writes to BOTH old and new
  - Backfill existing data
Phase 2: MIGRATE
  - Deploy: app reads from NEW, writes to BOTH
  - Verify data consistency
Phase 3: CONTRACT
  - Deploy: app only uses NEW
  - Drop old column/table in separate migration

Timeline Example

Day 1: Migration adds new_status column (nullable)
Day 1: Deploy app v2 — writes to both status and new_status
Day 2: Run backfill migration for existing rows
Day 3: Deploy app v3 — reads from new_status only
Day 7: Migration drops old status column

Anti-Patterns

| Anti-Pattern | Why It Fails | Better Approach | |-------------|-------------|-----------------| | Manual SQL in production | No audit trail, unrepeatable | Always use migration files | | Editing deployed migrations | Causes drift between environments | Create new migration instead | | NOT NULL without default | Locks table, rewrites all rows | Add nullable, backfill, then add constraint | | Inline index on large table | Blocks writes during build | CREATE INDEX CONCURRENTLY | | Schema + data in one migration | Hard to rollback, long transactions | Separate migrations | | Dropping column before removing code | Application errors on missing column | Remove code first, drop column next deploy |

← All skills