PostgreSQL Performance Optimization Guide

PostgreSQL is powerful, but getting the best performance requires understanding its internals. Here's my guide to optimization.

Query Optimization

EXPLAIN ANALYZE

Always use EXPLAIN ANALYZE to understand query execution:

EXPLAIN ANALYZE SELECT * FROM users WHERE email = 'test@example.com';

Index Types

• B-tree: Default, good for equality and range queries
• Hash: Equality only, rarely better than B-tree
• GIN: Full-text search, arrays, JSON
• GiST: Geometric data, ranges

Partial Indexes

Index only the rows you need.

Index-Only Scans

Include all needed columns in the index to avoid table lookups.

Configuration Tuning

Memory Settings

• shared_buffers: 25% of RAM
• work_mem: Depends on concurrent queries
• effective_cache_size: 50-75% of RAM

Connection Pooling

Use PgBouncer for connection management.

Common Pitfalls

1. N+1 queries: Use JOINs or batch loading
2. Missing indexes: Index foreign keys
3. Over-indexing: Indexes slow down writes
4. Not using VACUUM: Keep statistics updated

Monitoring

pg_stat_statements

Track query performance over time.

Slow Query Log

Log queries exceeding a threshold.

Conclusion

PostgreSQL optimization is iterative. Profile, optimize, measure, repeat.