Relational Databases

Purpose

This skill guides relational database selection and implementation across multiple languages. Choose the optimal database engine, ORM/query builder, and deployment strategy for transactional systems, CRUD applications, and structured data storage.

When to Use This Skill

Trigger this skill when:

• Building user authentication, content management, e-commerce applications
• Implementing CRUD operations (Create, Read, Update, Delete)
• Designing data models with relationships (users → posts, orders → items)
• Migrating schemas safely in production
• Setting up connection pooling for performance
• Evaluating serverless database options (Neon, PlanetScale, Turso)
• Integrating with frontend skills (forms, tables, dashboards, search-filter)

Skip this skill for:

• Time-series data at scale (use time-series databases)
• Real-time analytics (use columnar databases)
• Document-heavy workloads (use document databases)
• Key-value caching (use Redis, Memcached)

Quick Reference: Database Selection

Database Selection Decision Tree
═══════════════════════════════════════════════════════════

PRIMARY CONCERN?
├─ MAXIMUM FLEXIBILITY & EXTENSIONS (JSON, arrays, vector search)
│  └─ PostgreSQL
│     ├─ Serverless → Neon (scale-to-zero, database branching)
│     └─ Traditional → Self-hosted, AWS RDS, Google Cloud SQL
│
├─ EMBEDDED / EDGE DEPLOYMENT (local-first, global latency)
│  └─ SQLite or Turso
│     ├─ Global distribution → Turso (libSQL, edge replicas)
│     └─ Local-only → SQLite (embedded, zero-config)
│
├─ LEGACY SYSTEM / MYSQL REQUIRED
│  └─ MySQL
│     ├─ Serverless → PlanetScale (non-blocking migrations)
│     └─ Traditional → Self-hosted, AWS RDS, Google Cloud SQL
│
└─ RAPID PROTOTYPING
   ├─ Python → SQLModel (FastAPI) or SQLAlchemy 2.0
   ├─ TypeScript → Prisma (best DX) or Drizzle (performance)
   ├─ Rust → SQLx (compile-time checks)
   └─ Go → sqlc (type-safe code generation)