/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).
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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).
SKILL.md
database-migrations.SKILL.mdname: database-migrations
description: 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).
metadata:
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
1. **Every change is a migration** — never alter production databases manually 2. **Migrations are forward-only in production** — rollbacks use new forward migrations 3. **Schema and data migrations are separate** — never mix DDL and DML in one migration 4. **Test migrations against production-sized data** — a migration that works on 100 rows may lock on 10M 5. **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
Read more
name: database-migrations description: 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). metadata: 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
1. **Every change is a migration** — never alter production databases manually 2. **Migrations are forward-only in production** — rollbacks use new forward migrations 3. **Schema and data migrations are separate** — never mix DDL and DML in one migration 4. **Test migrations against production-sized data** — a migration that works on 100 rows may lock on 10M 5. **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
Your agent can write code, but ECC gives it a coordinated engineering system and toolbox: it plans before it builds, verifies changes with tests, reviews its own work from a fresh context, remembers what matters, and turns repeated wins into reusable skills
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