supabase-postgres-best-practices

Optimize slow Postgres queries by adding targeted indexes, rewriting query anti-patterns, and verifying improvements using EXPLAIN ANALYZE diagnostics. This approach reduces latency and improves scalability under load.

Prevent connection pool exhaustion by configuring connection pooling, setting strict timeouts, keeping transactions short, and applying safer concurrency patterns to reduce lock contention.

Row Level Security policies can become performance bottlenecks if poorly designed. You must optimize RLS policies to ensure security checks do not degrade query speed and scalability.

Design faster Postgres schemas by applying correct data types, constraints, and partitioning. Proper schema design reduces compute waste and improves reliability under heavy load.

Yes, you can review SQL during code review by requesting concrete incorrect versus correct rewrites, specific index additions, and necessary RLS changes to satisfy performance requirements.

Database locking under heavy load occurs from lock contention and long-running transactions. Resolve this by applying short transactions, timeout settings, and safer concurrency patterns.