Database Optimization Techniques

Database performance is crucial for application scalability. In this guide, we'll explore various optimization techniques that apply to most database systems.

Indexing Strategies

Proper indexing is the foundation of database performance:

-- Create an index on frequently queried columns
CREATE INDEX idx_users_email ON users(email);

-- Composite index for multi-column queries
CREATE INDEX idx_posts_user_status ON posts(user_id, status);

Query Optimization

Write efficient queries:

• Select only needed columns (SELECT id, name not SELECT *)
• Use EXPLAIN to analyze query plans
• Avoid N+1 queries with eager loading
• Use pagination for large result sets

Database Normalization

Balance between normalization and denormalization:

• Normalize to reduce data redundancy
• Denormalize strategically for read performance
• Use materialized views for complex aggregations

Connection Pooling and Caching

Advanced optimization techniques:

• Connection pooling reduces connection overhead
• Query caching for frequently accessed data
• Redis or Memcached for session and object caching

Whether you're using MySQL, PostgreSQL, or another database system, these techniques will help you build faster applications.