Database Implementation

When to use

• Setting up a new data access layer and choosing an ORM or query builder
• Writing migrations for schema changes
• Implementing transactions across multiple tables or services
• Configuring connection pooling for production
• Adding read replica routing for query scaling
• Optimizing slow queries (N+1, missing indexes, full scans)
• Writing database integration tests with Testcontainers
• Setting up factories or seed data

Core principles

1. ORM is a tool, SQL is the truth — know what queries your ORM generates; use EXPLAIN ANALYZE
2. Migrations are immutable contracts — never modify a migration applied to any shared environment
3. Pooling is not optional — one connection per request = death in production
4. Transactions stay short — locks held across network calls cause cascading timeouts
5. Test against the real database — in-memory SQLite mocks hide Postgres-specific bugs

Reference Files

• references/orm-selection.md — comparison tables for all ORMs and query builders across Node.js, Python, Go, Rust, JVM, Ruby, Elixir, and .NET; pick before writing any data layer code
• references/prisma-drizzle-patterns.md — Prisma schema definition, interactive transactions, raw queries, client extensions, Accelerate caching, Pulse change streams; Drizzle schema, relations, queries, and Kit migrations
• references/polyglot-orm-patterns.md — production patterns for SQLAlchemy 2.0 async, GORM with hooks and Gen, Diesel compile-time queries, EF Core 8 with interceptors, Ecto changesets and Multi, and Exposed DSL
• references/migrations-pooling-replicas.md — migration rules (zero-downtime patterns, idempotency), connection pool sizing per stack, read replica routing, query optimization checklist, and transaction isolation guidelines
• references/testing-seeding.md — Testcontainers setup for Node.js/Python/Go, pg_tmp for fast local tests, fishery/factory_boy database factories, and seed script best practices