PostgreSQL Performance Cookbook — Query Optimization for Production Databases
Slow queries don't announce themselves in development. They wait until you have real data and real traffic, then they take down your app at 2pm on a Tuesday. This cookbook gives you 47 production-tested fixes — so you know what to do before and after that happens.Who This Is ForBackend developers, SaaS engineers, and indie hackers running PostgreSQL in production. Useful whether you're pre-scale and want to build it right, or post-scale and chasing a specific performance problem.What's Inside Query optimization — EXPLAIN ANALYZE patterns, index-scan vs. seq-scan diagnosis, rewriting slow JOINs, and CTE optimization Index strategy — when to use B-tree, GIN, GiST, partial indexes, covering indexes, and composite indexes. Index bloat diagnosis and REINDEX patterns. N+1 elimination — identifying N+1 in application logs, fixing with JOINs, CTEs, and dataloader patterns Connection pooling — PgBouncer setup, pool sizing formulas, connection exhaustion diagnosis, and Supabase-specific pooler configuration Vacuum and autovacuum tuning — understanding table bloat, configuring autovacuum for high-write tables, and manual vacuum runbooks Partitioning — range and list partitioning for time-series and multi-tenant data Full-text search — tsvector columns, GIN indexes, weighted ranking, and trigram search with pg_trgm Monitoring queries — pg_stat_statements, long-running query detection, lock monitoring After This CookbookYou'll diagnose slow queries in under 10 minutes. You'll know exactly which index to add for a given query pattern. You'll have a connection pooling setup that handles traffic spikes without exhaustion errors. Every fix includes the SQL, the before/after explain output, and the reasoning.$47. One fewer outage or one hour of consulting time you didn't need to buy. 30-day refund if it doesn't deliver.
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