Database Migration Patterns

Schema Evolution Strategies

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 changes on critical tables | | Lazy Migration | Medium | None | Large tables where bulk migration is too slow | | Big Bang | High | Yes | Dev/staging or small datasets only |

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

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Zero-Downtime Patterns

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

Operation	Pattern	Key Constraint
Add column	Nullable first	Never add NOT NULL without default on large tables
Rename column

Expand-contract | Add new → dual-write → backfill → switch reads → drop old |
| Drop column | Deprecate first | Stop reading → stop writing → deploy → drop |
| Change type | Parallel column | Add new type → dual-write + cast → switch → drop old |
| Add index | Concurrent | CREATE INDEX CONCURRENTLY — don't wrap in transaction |
| Split table | Extract + FK | Create new → backfill → add FK → update queries → drop old columns |
| Change constraint | Two-phase | Add NOT VALID → VALIDATE CONSTRAINT separately |
| Add enum value | Append only | Never remove or rename existing values |

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Migration Tools

Tool	Ecosystem	Style	Key Strength
Prisma Migrate	TypeScript/Node	Declarative (schema diff)	ORM integration, shadow DB
Knex

JavaScript/Node | Imperative (up/down) | Lightweight, flexible |
| Drizzle Kit | TypeScript/Node | Declarative (schema diff) | Type-safe, SQL-like |
| Alembic | Python | Imperative (upgrade/downgrade) | Granular control, autogenerate |
| Django Migrations | Python/Django | Declarative (model diff) | Auto-detection |
| Flyway | JVM / CLI | SQL file versioning | Simple, wide DB support |
| golang-migrate | Go / CLI | SQL (up/down files) | Minimal, embeddable |
| Atlas | Go / CLI | Declarative (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.

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Rollback Strategies

Approach	When to Use
Reversible (up + down)	Schema-only changes, early-stage products
Forward-only (corrective migration)

Data-destructive changes, production at scale |
| Hybrid | Reversible for schema, forward-only for data |

Data Preservation

1. 1. Soft-delete columns — rename with _deprecated suffix instead of dropping
2. Snapshot tables — INLINECODE5
3. Point-in-time recovery — ensure WAL archiving covers migration windows
4. Logical backups — pg_dump of affected tables before migration

Blue-Green Database

CODEBLOCK0

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Data Migration Patterns

Backfill Strategies

Strategy	Best For
Inline backfill	Small tables (< 100K rows)
Batched backfill

Medium tables (100K–10M rows) | | Background job | Large tables (10M+ rows) | | Lazy backfill | When immediate consistency not required |

Batch Processing

CODEBLOCK1

Dual-Write Period

For expand-contract and parallel change:

1. 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

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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

CODEBLOCK2

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

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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

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NEVER Do

1. 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