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StackPractices
intermediate By Mathias Paulenko

Database Migrations Safely

How to run database schema migrations without downtime or data loss.

Topics: databases

Note: This guide follows English-language naming conventions and terminology standards common in international development teams. Examples use English identifiers and comments to maximize compatibility across codebases and tooling.

Overview

Database migrations evolve your schema as your application changes. Unsafe migrations — like adding a non-nullable column to a large table or dropping a column still referenced by old code — can cause downtime, data loss, or deployment failures. The solution below covers safe migration patterns using Alembic (Python), Knex.js (JavaScript), and Flyway (Java), plus zero-downtime deployment strategies.

When to Use

Use this resource when:

  • You’re deploying schema changes to a production database with live traffic. See Database Migrations for tooling overview.
  • You need to add, rename, or remove columns without breaking running applications. See Input Validation for schema safety.
  • You’re migrating data between tables or formats. See Data Validation for integrity checks.
  • You want to establish a rollback plan before running any migration. See Retry Logic for recovery patterns.

Solution

Python (Alembic)

# migration: add new nullable column, backfill, then make non-nullable
from alembic import op
import sqlalchemy as sa
from sqlalchemy.sql import table, column

revision = "abc123"
down_revision = "xyz789"

def upgrade():
    # Step 1: Add as nullable so existing rows don't fail
    op.add_column("users", sa.Column("display_name", sa.String(255), nullable=True))

    # Step 2: Backfill with default value
    users = table("users", column("display_name"))
    op.execute(users.update().values(display_name="Unnamed User"))

    # Step 3: Now safe to make non-nullable
    op.alter_column("users", "display_name", nullable=False)

def downgrade():
    op.drop_column("users", "display_name")

JavaScript (Knex.js)

// migration: safe column rename using views or dual writes
exports.up = async function(knex) {
  // Phase 1: Add new column, keep old column
  await knex.schema.table("users", (table) => {
    table.string("full_name", 255).nullable();
  });

  // Phase 2: Backfill from old column
  await knex("users").whereNull("full_name").update({
    full_name: knex.ref("name"),
  });

  // Phase 3: Make non-nullable in a later deploy after all code writes new column
  // await knex.schema.table("users", (table) => { table.string("full_name").notNullable().alter(); });
};

exports.down = async function(knex) {
  await knex.schema.table("users", (table) => {
    table.dropColumn("full_name");
  });
};

Java (Flyway)

// V2__add_user_status.sql
-- Add enum column as text first, migrate data, then add CHECK constraint in V3
ALTER TABLE users ADD COLUMN status VARCHAR(20) NULL;

UPDATE users SET status = 'active' WHERE status IS NULL;

-- V3__enforce_user_status.sql (deployed in next release)
-- ALTER TABLE users ALTER COLUMN status SET NOT NULL;
-- ALTER TABLE users ADD CONSTRAINT chk_status CHECK (status IN ('active', 'inactive', 'banned'));

Explanation

Safe migrations follow the expand-contract pattern for any breaking change:

  1. Expand: Add the new schema element (column, table, index) alongside the old one. Keep it optional.
  2. Migrate: Deploy application code that writes to both old and new structures (dual-write).
  3. Contract: Once all old code paths are gone, make the new structure required and remove the old one.

This pattern guarantees that any running instance of your app (including during rolling deploys) can read and write without errors.

Variants

StrategyWhen to UseExample
Expand-ContractRenaming columns, changing typesAdd full_name, dual-write, drop name
Online DDL (pt-online-schema-change)MySQL large tablesAlter 100M+ row tables without locks
Concurrent index creationPostgreSQL indexesCREATE INDEX CONCURRENTLY to avoid table locks
Backfill in batchesLarge table migrationsUpdate 10k rows per transaction to avoid long locks
Blue/Green deployCritical systemsRun new schema on green, switch traffic, then drop old

What Works

  • Always make new columns nullable first: Existing rows must not fail during the migration.
  • Backfill before making non-nullable: Update existing rows with sensible defaults before adding NOT NULL.
  • Add indexes concurrently: On PostgreSQL, use CREATE INDEX CONCURRENTLY; on MySQL, use pt-online-schema-change or ALGORITHM=INPLACE.
  • Keep migrations idempotent: Running the same migration twice should be safe.
  • Version your migrations and test on a copy: Restore a production backup to a staging environment and run the full migration suite before production.

Common Mistakes

  • Adding a non-nullable column without a default: Locks the table while populating every row, potentially for hours.
  • Dropping a column still read by old code: Rolling deployments run old and new code simultaneously; the old code will crash.
  • Running heavy migrations during peak traffic: Schedule schema changes during maintenance windows or use online DDL tools.
  • No rollback plan: Every migration should have a tested downgrade or revert script.
  • Ignoring lock timeouts: Long-running migrations can exceed statement timeouts and leave the database in a half-migrated state.

Frequently Asked Questions

How do I rename a column without downtime?

Use the expand-contract pattern: (1) Add the new column, (2) Update app code to write to both columns, (3) Backfill old data to the new column, (4) Switch reads to the new column, (5) Remove the old column. This spans multiple deploys but is the only safe way in production.

Can I run migrations automatically on app startup?

Only for non-breaking, fast migrations (adding a nullable column, creating an index concurrently). For destructive or slow migrations (dropping columns, changing types, backfilling data), run them manually during a maintenance window or via a CI/CD pipeline with approval gates. Never auto-run risky migrations.

How do I handle migrations on large tables (100M+ rows)?

  • Use online DDL tools (pt-online-schema-change for MySQL, pg_repack for PostgreSQL)
  • Batch backfills in chunks of 1,000-10,000 rows with COMMIT between batches
  • Add indexes concurrently to avoid locking
  • Run during low-traffic windows even with online tools
  • Monitor replication lag if you’re running against a primary with replicas. See Read Replicas for replication management.

Batch backfill with Alembic

from alembic import op
import sqlalchemy as sa
from sqlalchemy.sql import table, column

def upgrade():
    op.add_column("orders", sa.Column("status", sa.String(20), nullable=True))

    # Batch backfill in chunks of 5000
    conn = op.get_bind()
    while True:
        result = conn.execute(sa.text("""
            UPDATE orders
            SET status = 'completed'
            WHERE id IN (
                SELECT id FROM orders
                WHERE status IS NULL
                LIMIT 5000
            )
            RETURNING id
        """))
        if result.rowcount == 0:
            break
        print(f"Backfilled {result.rowcount} rows")

    # Add check constraint
    op.create_check_constraint(
        "chk_order_status",
        "orders",
        "status IN ('pending', 'processing', 'completed', 'cancelled')"
    )

def downgrade():
    op.drop_constraint("chk_order_status", "orders")
    op.drop_column("orders", "status")

Rollback strategy with Knex.js

exports.up = async function(knex) {
    await knex.schema.createTable('feature_flags', (table) => {
        table.increments('id');
        table.string('name', 100).notNullable().unique();
        table.boolean('enabled').defaultTo(false);
        table.timestamp('created_at').defaultTo(knex.fn.now());
    });

    // Seed initial flags
    await knex('feature_flags').insert([
        { name: 'new_checkout', enabled: false },
        { name: 'dark_mode', enabled: true }
    ]);
};

exports.down = async function(knex) {
    // Safe rollback: drop table only if it exists
    await knex.schema.dropTableIfExists('feature_flags');
};

Testing migrations with Flyway

// V4__add_indexes.sql
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_users_email
ON users (email);

// V5__add_foreign_key.sql
-- Add FK as NOT VALID first (fast, no table scan)
ALTER TABLE orders
  ADD CONSTRAINT fk_orders_user_id
  FOREIGN KEY (user_id) REFERENCES users(id)
  NOT VALID;

-- Validate in a separate step (scans but doesn't block writes)
ALTER TABLE orders VALIDATE CONSTRAINT fk_orders_user_id;
# Test migrations on a copy of production data
flyway -url=jdbc:postgresql://staging:5432/mydb \
  -user=migration_user \
  -password=$STAGING_DB_PASS \
  -locations=filesystem:db/migrations \
  -cleanDisabled=false \
  migrate

# Verify with dry run
flyway -url=jdbc:postgresql://staging:5432/mydb \
  -user=migration_user \
  -password=$STAGING_DB_PASS \
  -locations=filesystem:db/migrations \
  info

Additional Best Practices

  1. Set lock_timeout before DDL. Prevents migrations from waiting indefinitely for locks:
SET lock_timeout = '10s';
ALTER TABLE users ADD COLUMN phone VARCHAR(20);
  1. Use statement_timeout for batch operations. Aborts backfills that run too long:
SET statement_timeout = '60s';
  1. Run ANALYZE after large backfills. Updates planner statistics so queries choose optimal plans:
ANALYZE users;
  1. Create indexes concurrently. CREATE INDEX CONCURRENTLY in PostgreSQL avoids blocking writes but cannot run inside a transaction.

  2. Use feature flags for schema-dependent code. Decouple code deploys from schema changes:

if feature_flags.is_enabled("use_full_name"):
    display = user.full_name
else:
    display = user.name

Additional Common Mistakes

  1. Adding a column with a volatile default. ADD COLUMN ... DEFAULT random() rewrites the entire table in PostgreSQL < 11. Use nullable + backfill instead.
  2. Not testing rollback scripts. A rollback that fails is worse than no rollback. Test downgrade() on a staging copy.
  3. Running migrations inside application startup for large changes. Use a separate migration step in CI/CD with approval gates.
  4. Forgetting to update statistics. After large data changes, ANALYZE is needed for the query planner to pick correct plans.
  5. Dropping a column before all code stops reading it. During rolling deploys, old instances may still reference the dropped column.

Additional FAQ

How do I add a foreign key without locking?

In PostgreSQL, add the constraint as NOT VALID first, then validate separately:

ALTER TABLE orders
  ADD CONSTRAINT fk_orders_user_id
  FOREIGN KEY (user_id) REFERENCES users(id)
  NOT VALID;

ALTER TABLE orders VALIDATE CONSTRAINT fk_orders_user_id;

What is the difference between gh-ost and pt-online-schema-change?

Both perform online schema changes for MySQL. gh-ost (GitHub) uses binlog for sync and avoids triggers. pt-online-schema-change uses triggers. gh-ost is preferred for high-write environments.

How do I handle migrations in a blue-green deployment?

Deploy schema changes to the green environment first. Both blue and green must work with the new schema. Use expand-contract: expand schema, deploy new code, switch traffic, then contract old schema.

Performance Tips

  1. Batch backfills with LIMIT and sleep. Process 1,000-10,000 rows per batch with short pauses to minimize replication lag and lock contention.

  2. Use CREATE INDEX CONCURRENTLY for all production indexes. Takes longer but doesn’t block writes. Monitor progress via pg_stat_progress_create_index.

  3. Configure work_mem for migration sessions. Increase it for large batch operations:

SET work_mem = '256MB';
  1. Monitor pg_stat_activity during migrations. Watch for long-running queries and lock waits:
SELECT pid, state, wait_event_type, wait_event,
       now() - query_start AS duration, query
FROM pg_stat_activity
WHERE state != 'idle'
ORDER BY duration DESC;
  1. Use pg_repack for table bloat. After large backfills, tables and indexes can become bloated. pg_repack rebuilds tables without exclusive locks.