supabase-postgres-best-practices

To fix slow Postgres queries on Supabase, analyze your SQL with EXPLAIN plans to identify bottlenecks, then apply suggested index rewrites and connection pooling configurations. This reduces query latency and improves dashboard load times.

The best way to design indexes for Supabase Postgres is to implement partial and composite indexes based on your specific access patterns. Proper schema design and indexing reduce table bloat and significantly improve data retrieval speeds.

Row-level security (RLS) policies can degrade Supabase database performance if not properly optimized. Analyzing RLS configurations alongside query plans helps identify policy bottlenecks and ensures secure data access without sacrificing query speed.

Yes, you can configure connection pooling to improve Supabase Postgres concurrency. Proper connection management prevents connection exhaustion during traffic spikes and allows the database to handle simultaneous requests efficiently.

Your Supabase Postgres query might ignore indexes due to inefficient schema patterns, outdated statistics, or suboptimal query structures. Reviewing the EXPLAIN plan reveals sequential scans and highlights necessary query rewrites or index adjustments.