Database Migration Plan

Before you start

Gather the following from the user:

1. What schema change is needed? (Add column, rename column, change type, add/drop index, create/drop table, split table)
2. Which database engine? (PostgreSQL, MySQL, SQL Server, or engine-agnostic)
3. Is zero-downtime required? (Can the application tolerate maintenance windows?)
4. What is the table size? (Row count and data size — this determines strategy)
5. Are there dependent applications? (Other services reading/writing this table)
6. What ORM or migration tool is in use? (Prisma, Drizzle, Knex, Flyway, Alembic, ActiveRecord, raw SQL)

If the user says "add a column to the users table," push back: "How many rows? Is the app deployed with zero-downtime requirements? Is the column nullable or does it need a default? Other services reading this table?"

This skill covers schema-level DDL changes. For moving data between systems or ETL pipelines, see the data-migration-plan skill instead.

Procedure

Step 1: Classify the migration risk

Change type	Lock risk	Data risk	Typical approach
Add nullable column	Low	None	Single migration
Add column with default	Medium (engine-dependent)	None	Check engine behavior
Add index	Medium-High	None	CREATE INDEX CONCURRENTLY
Drop column	Low	High (data loss)	Multi-phase
Rename column	High	Medium	Multi-phase with alias
Change column type	High	High	Multi-phase with dual-write
Drop table	Low	High (data loss)	Multi-phase with grace period
Split/merge tables	High	High	Multi-phase with dual-write

For medium or high risk changes, use the multi-phase approach in Step 3.

Step 2: Write the migration script

Every migration must have an up and down script:

-- Migration: 20240115_001_add_status_to_orders
-- Description: Add status column to orders table for fulfillment tracking

-- UP
ALTER TABLE orders ADD COLUMN status VARCHAR(32) NULL;

-- DOWN
ALTER TABLE orders DROP COLUMN status;

Rules for migration scripts:

• Name with timestamp prefix and sequential number: YYYYMMDD_NNN_description
• One logical change per migration file — never bundle unrelated changes
• DOWN script must be tested and produce the exact prior schema
• Include comments stating what the migration does and why
• For large tables, include estimated execution time

Step 3: Multi-phase migration pattern

For changes that require zero-downtime on production tables:

1. Expand — Add the new structure alongside the old (e.g., ALTER TABLE ADD COLUMN status_new NULL).
2. Dual-write — Deploy code that writes to both old and new. Reads prefer new, fall back to old.
3. Backfill — Migrate existing data in batches (5,000-50,000 rows per commit). Monitor replication lag between batches.
4. Cutover — Switch all reads and writes to the new structure. Verify no queries reference the old column in production logs.
5. Contract — Drop the old structure (ALTER TABLE DROP COLUMN).

Each phase is a separate deployment. Never combine phases into one release.

Step 4: Handle engine-specific concerns

PostgreSQL: ADD COLUMN with non-volatile default is metadata-only in PG 11+. Use CREATE INDEX CONCURRENTLY (cannot run inside a transaction). ALTER COLUMN TYPE rewrites the table on large tables — use multi-phase.

MySQL (InnoDB): Use ALGORITHM=INPLACE, LOCK=NONE where supported. Adding a column with default rewrites the table in MySQL < 8.0.12 — use pt-online-schema-change or gh-ost for large tables.

Step 5: Write the rollback plan

For each migration phase, document:

Phase: [N]
Rollback trigger: [What condition triggers rollback]
Rollback steps:
  1. [Exact SQL or deployment step]
  2. [Verify step]
Time estimate: [How long rollback takes]
Data impact: [What data is lost on rollback, if any]

Rollback must be tested in staging before production deployment. If the DOWN migration involves data loss, document what is lost and whether it is recoverable from backups.

Step 6: Define the verification plan

After each phase, verify three areas:

• Schema: Run \d table_name (PG) or DESCRIBE table_name (MySQL). Compare against expected state.
• Data: Row count matches pre-migration. Null check on new columns shows 0 after backfill. Spot check sample rows.
• Application: Health checks return 200, error rates unchanged, query latency p99 within baseline.

Quality checklist

Before delivering the migration plan, verify:

• Every migration has both UP and DOWN scripts
• High-risk changes use the multi-phase expand/migrate/contract pattern
• Backfill runs in batches with commit points, not one massive UPDATE
• Rollback plan exists for each phase with explicit triggers and time estimates
• Engine-specific locking behavior is accounted for
• Verification queries are included for schema, data integrity, and performance
• The plan distinguishes between schema changes (this skill) and data movement (data-migration-plan)

Common mistakes

• Running ALTER TABLE on a large table without checking lock behavior. A table-rewriting ALTER on a 100M-row table locks writes for minutes. Check your engine version's online DDL support first.
• Combining expand and contract in one deployment. If the new schema has a bug, you cannot roll back without data loss. Always separate by at least one deployment cycle.
• Backfilling without batching. UPDATE orders SET x = y on 50M rows creates a massive transaction, bloats WAL/binlog, and may cause replication lag or OOM. Batch in chunks of 5,000-50,000.
• Skipping the DOWN migration. "We will never roll back" is not a plan. Write and test the rollback script before running the forward migration.
• Forgetting dependent services. Another team's service may query the column you are renaming. Check for cross-service dependencies before dropping or renaming.
• Not monitoring replication lag during backfill. On replicated databases, large writes increase replication lag. Pause between batches if lag exceeds your threshold.