PostgreSQL Performance Optimization: A Practical Guide

Database performance work should begin with evidence. Slow APIs often look like a backend problem, but the root cause can be missing indexes, large payloads, N+1 queries, or queries that ask the database to do too much at once.

Measure The Query

Use query logs, application timing, and EXPLAIN ANALYZE to understand what PostgreSQL is actually doing. The plan will usually tell you whether the database is scanning too many rows, sorting too much data, or joining inefficiently.

EXPLAIN ANALYZE
SELECT id, email, created_at
FROM users
WHERE workspace_id = $1
ORDER BY created_at DESC
LIMIT 25;

Index For Access Patterns

Good indexes follow the way the product reads data. If most screens filter by workspace and sort by creation time, a compound index can be more useful than two unrelated single-column indexes.

CREATE INDEX users_workspace_created_at_idx
ON users (workspace_id, created_at DESC);

Avoid N+1 Queries

The N+1 pattern appears when the app loads one list, then performs another query for each item. It feels fine with ten records and becomes painful with real data.

• Load related records with joins when the relationship is simple.
• Use selective includes in your ORM instead of fetching entire objects.
• Paginate lists before joining large related tables.
• Watch query counts in development, not only production.