supabase-postgres-best-practices

To optimize slow PostgreSQL queries, you need to identify missing indexes and rewrite inefficient query patterns. This Skill provides prioritized rules with incorrect versus correct SQL examples to guide query optimization and improve database performance.

PostgreSQL schema design best practices involve selecting appropriate data types, applying constraints, and implementing partitioning. These guidelines help structure your database efficiently to prevent performance bottlenecks as your data grows.

Connection pooling optimizes PostgreSQL performance by managing database connections and timeouts to prevent resource exhaustion. Configuring pooling properly ensures your application handles concurrent requests without overwhelming the database server.

You should use composite indexes in PostgreSQL when queries filter or sort on multiple columns simultaneously. This Skill details how to choose the right index types and add missing indexes to significantly speed up complex query execution.

These PostgreSQL performance optimization guidelines are maintained by Supabase but apply to general Postgres databases. The rules cover universal concepts like query optimization, schema design, and connection management applicable across environments.

Supabase database resource exhaustion often stems from inefficient SQL queries, missing indexes, or unoptimized connection management. Applying targeted performance rules can identify problematic patterns and provide actionable advice to resolve slowdowns.