Data & analysis

database-migrations

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Safe, zero-downtime database migration strategies — schema evolution, rollback planning, data migration, tooling, and anti-pattern avoidance for production systems. Use when planning schema changes, writing migrations, or reviewing migration safety.

What it does

| Strategy | Risk | Downtime | Best For | |----------|------|----------|----------| | **Additive-Only** | Very Low | None | APIs with backward-compatibility guarantees | | **Expand-Contract** | Low | None | Renaming, restructuring, type changes | | **Parallel Change** | Low | None | High-risk chang…

The skill document

Database Migration Patterns

Schema Evolution Strategies

StrategyRiskDowntimeBest For
Additive-OnlyVery LowNoneAPIs with backward-compatibility guarantees
Expand-ContractLowNoneRenaming, restructuring, type changes
Parallel ChangeLowNoneHigh-risk changes on critical tables
Lazy MigrationMediumNoneLarge tables where bulk migration is too slow
Big BangHighYesDev/staging or small datasets only

Default to Additive-Only. Escalate to Expand-Contract only when you must modify or remove existing structures.


Zero-Downtime Patterns

Every production migration must avoid locking tables or breaking running application code.

OperationPatternKey Constraint
Add columnNullable firstNever add NOT NULL without default on large tables
Rename columnExpand-contractAdd new → dual-write → backfill → switch reads → drop old
Drop columnDeprecate firstStop reading → stop writing → deploy → drop
Change typeParallel columnAdd new type → dual-write + cast → switch → drop old
Add indexConcurrentCREATE INDEX CONCURRENTLY — don't wrap in transaction
Split tableExtract + FKCreate new → backfill → add FK → update queries → drop old columns
Change constraintTwo-phaseAdd NOT VALIDVALIDATE CONSTRAINT separately
Add enum valueAppend onlyNever remove or rename existing values

Migration Tools

ToolEcosystemStyleKey Strength
Prisma MigrateTypeScript/NodeDeclarative (schema diff)ORM integration, shadow DB
KnexJavaScript/NodeImperative (up/down)Lightweight, flexible
Drizzle KitTypeScript/NodeDeclarative (schema diff)Type-safe, SQL-like
AlembicPythonImperative (upgrade/downgrade)Granular control, autogenerate
Django MigrationsPython/DjangoDeclarative (model diff)Auto-detection
FlywayJVM / CLISQL file versioningSimple, wide DB support
golang-migrateGo / CLISQL (up/down files)Minimal, embeddable
AtlasGo / CLIDeclarative (HCL/SQL diff)Schema-as-code, linting, CI

Match the tool to your ORM and deployment pipeline. Prefer declarative for simple schemas, imperative for fine-grained data manipulation.


Rollback Strategies

ApproachWhen to Use
Reversible (up + down)Schema-only changes, early-stage products
Forward-only (corrective migration)Data-destructive changes, production at scale
HybridReversible for schema, forward-only for data

Data Preservation

  1. Soft-delete columns — rename with _deprecated suffix instead of dropping
  2. Snapshot tablesCREATE TABLE _backup__ AS SELECT * FROM
  3. Point-in-time recovery — ensure WAL archiving covers migration windows
  4. Logical backupspg_dump of affected tables before migration

Blue-Green Database

1. Replicate primary → secondary (green)
2. Apply migration to green
3. Run validation suite against green
4. Switch traffic to green
5. Keep blue as rollback target (N hours)
6. Decommission blue after confidence window

Data Migration Patterns

Backfill Strategies

StrategyBest For
Inline backfillSmall tables (< 100K rows)
Batched backfillMedium tables (100K–10M rows)
Background jobLarge tables (10M+ rows)
Lazy backfillWhen immediate consistency not required

Batch Processing

DO $$
DECLARE
  batch_size INT := 1000;
  rows_updated INT;
BEGIN
  LOOP
    UPDATE my_table
    SET new_col = compute_value(old_col)
    WHERE id IN (
      SELECT id FROM my_table
      WHERE new_col IS NULL
      LIMIT batch_size
      FOR UPDATE SKIP LOCKED
    );
    GET DIAGNOSTICS rows_updated = ROW_COUNT;
    EXIT WHEN rows_updated = 0;
    PERFORM pg_sleep(0.1);  -- throttle to reduce lock pressure
    COMMIT;
  END LOOP;
END $$;

Dual-Write Period

For expand-contract and parallel change:

  1. Dual-write — application writes to both old and new columns/tables
  2. Backfill — fill new structure with historical data
  3. Verify — assert consistency (row counts, checksums)
  4. Cut over — switch reads to new, stop writing to old
  5. Cleanup — drop old structure after cool-down period

Testing Migrations

Test Against Production-Like Data

  • Never test against empty or synthetic data only
  • Use anonymized production snapshots
  • Match data volume — a migration working on 1K rows may lock on 10M
  • Reproduce edge cases: NULLs, empty strings, max-length, unicode

Migration CI Pipeline

- name: Test migrations
  steps:
    - run: docker compose up -d db
    - run: npm run migrate:up        # apply all
    - run: npm run migrate:down      # rollback all
    - run: npm run migrate:up        # re-apply (idempotency)
    - run: npm run test:integration  # validate app
    - run: npm run migrate:status    # no pending

Every migration PR must pass: up → down → up → tests.


Migration Checklist

Pre-Migration

  • Tested against production-like data volume
  • Rollback written and tested
  • Backup of affected tables created
  • App code compatible with both old and new schema
  • Execution time benchmarked on staging
  • Lock impact analyzed
  • Replication lag monitoring in place

During Migration

  • Monitor lock waits and active queries
  • Monitor replication lag
  • Watch for error rate spikes
  • Keep rollback command ready

Post-Migration

  • Schema matches expected state
  • Integration tests pass against migrated DB
  • Data integrity validated (row counts, checksums)
  • ORM schema / type definitions updated
  • Deprecated structures cleaned up after cool-down
  • Migration documented in team runbook

NEVER Do

  1. NEVER run untested migrations directly in production
  2. NEVER drop a column without first removing all application references and deploying
  3. NEVER add NOT NULL to a large table without a default value in a single statement
  4. NEVER mix schema DDL and data mutations in the same migration file
  5. NEVER skip the dual-write phase when renaming columns in a live system
  6. NEVER assume migrations are instantaneous — always benchmark on production-scale data
  7. NEVER disable foreign key checks to "speed up" migrations in production
  8. NEVER deploy application code that depends on a schema change before the migration has completed

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