data-management

name: data-management description: Design and manage data storage effectively. Use when working with databases, schemas, or data migrations. Covers schema design, migrations, and data integrity.

Data Management

Workflows

• Schema Design: Define tables, relationships, constraints
• Migrations: Version control schema changes
• Indexing: Add indexes for query performance
• Backup: Ensure data recovery capability

Schema Design Principles

Normalization

• 1NF: Atomic values, no repeating groups
• 2NF: No partial dependencies
• 3NF: No transitive dependencies

When to Denormalize

• Read-heavy workloads
• Reporting/analytics
• Caching layers

Migration Best Practices

Forward-Only Migrations

Each migration should be a single forward step.

-- migrations/001_create_users.sql
CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  email VARCHAR(255) NOT NULL UNIQUE,
  created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

CREATE INDEX idx_users_email ON users(email);

Safe Migrations

• Add columns as nullable first
• Create indexes concurrently
• Never drop columns in the same deploy

Indexing Strategy

-- B-tree (default): Equality and range queries
CREATE INDEX idx_users_email ON users(email);

-- Partial index: When you query a subset
CREATE INDEX idx_active_users ON users(id) WHERE active = true;

-- Composite index: Multiple columns
CREATE INDEX idx_orders_user_date ON orders(user_id, created_at DESC);

Connection Management

// Use connection pooling
const pool = new Pool({
  max: 20,                    // Max connections
  idleTimeoutMillis: 30000,   // Close idle connections
  connectionTimeoutMillis: 2000
});

Data Integrity

• Use foreign key constraints
• Add NOT NULL where appropriate
• Use CHECK constraints for validation
• Consider using ENUM types for fixed values