PostgreSQL Performance Tuning: Practical Guide for Enterprise Applications

PostgreSQL performs well out of the box, but enterprise workloads require tuning.

Query Analysis

EXPLAIN ANALYZE is your friend. Understand query plans, identify sequential scans, and find missing indexes.

Index Strategies

• B-tree for equality and range queries
• GIN for full-text and JSON
• Partial indexes for filtered queries
• Expression indexes for computed values

Configuration Tuning

Key parameters:

• shared_buffers (25% of RAM)
• effective_cache_size (75% of RAM)
• work_mem (per-query memory)
• maintenance_work_mem (for vacuum/index builds)

Connection Management

Use connection pooling (PgBouncer). Don't let applications hold connections indefinitely. Monitor connection count and wait times.