How to diagnose and improve PostgreSQL performance

A measured approach to PostgreSQL queries, indexes, connection use, maintenance and application performance. This guide explains the practical decisions behind it and what those decisions mean for the people using and operating the product.

Begin with slow user journeys

Measure complete requests with realistic data before changing configuration. Query logs and application traces show whether time is lost in one expensive statement or hundreds of avoidable calls.

Use EXPLAIN with care

Execution plans reveal scans, joins, estimates and index use. EXPLAIN ANALYZE executes the query, so potentially expensive or modifying statements require a safe environment and informed handling.

Keep statistics and tables healthy

PostgreSQL relies on current statistics and vacuuming to make good decisions and reclaim storage. Autovacuum should be monitored and tuned around workload rather than disabled when it becomes visible.

Control connections

Every database connection consumes resources. Pooling and sensible worker limits protect the server from traffic bursts while preventing the application from waiting behind an unnecessarily small pool.

Scale after removing waste

Caching, replicas and larger machines help appropriate workloads, but cannot repair an uncontrolled query pattern. Optimise measured bottlenecks first and verify the improvement from the user’s perspective.

Explore our Postgresql technology page or discuss the requirement with Noviom Labs.