PostgreSQL Performance Optimization Guide
Advanced techniques for optimizing PostgreSQL performance: indexing strategies, query optimization, and configuration tuning.

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
- N+1 queries: Use JOINs or batch loading
- Missing indexes: Index foreign keys
- Over-indexing: Indexes slow down writes
- 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.
