supabase-postgres-best-practices

To optimize slow Postgres queries in Supabase, analyze execution plans using EXPLAIN ANALYZE, add missing indexes, and fix inefficient join or filter patterns by applying incorrect-versus-correct SQL examples aligned with Supabase best practices.

The best way to design a scalable Postgres schema is to use proper primary keys, implement composite, covering, and partial indexes, index foreign keys, and apply table partitioning to improve both durability and query speed.

Row-level security (RLS) for multi-tenant access in Postgres works by enforcing performant policy patterns that restrict data access at the row level, ensuring correct and safe multi-tenant data isolation without relying solely on application logic.

To prevent Postgres connection exhaustion in Supabase, apply connection pooling best practices and tune connection behavior to manage concurrent database connections efficiently, avoiding exhausted connection limits during high traffic.

You need partial or covering indexes in Postgres when optimizing queries that filter on specific subsets of data or require additional columns without table lookups, significantly improving query performance and reducing I/O overhead.