# Using Relational Databases

Relational database implementation across Python, Rust, Go, and TypeScript.

- Repository: https://github.com/ancoleman/ai-design-components (526 stars)
- Category: Data and ML
- License: MIT
- Last updated: 2025-12-11
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add ancoleman/ai-design-components --skill using-relational-databases -g -a claude-code -y`
Codex: `npx skills add ancoleman/ai-design-components --skill using-relational-databases -g -a codex -y`
Cursor: `npx skills add ancoleman/ai-design-components --skill using-relational-databases -g -a cursor -y`
Gemini CLI: `npx skills add ancoleman/ai-design-components --skill using-relational-databases -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add ancoleman/ai-design-components`

## Description

Relational database implementation across Python, Rust, Go, and TypeScript. Use when building CRUD applications, transactional systems, or structured data storage. Covers PostgreSQL (primary), MySQL, SQLite, ORMs (SQLAlchemy, Prisma, SeaORM, GORM), query builders (Drizzle, sqlc, SQLx), migrations, connection pooling, and serverless databases (Neon, PlanetScale, Turso).

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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)
```

The rest: https://github.com/ancoleman/ai-design-components/blob/HEAD/skills/using-relational-databases/SKILL.md