supabase-postgres-best-practices

Postgres indexing strategies improve query speed by applying deterministic rules to choose the right index types for your schema. This Skill provides structured guidance and SQL examples to fix suboptimal indexing, reducing latency and increasing throughput.

Table partitioning is needed when managing large datasets that cause query latency and vacuum overhead. This Skill provides structured guidance to design scalable schemas and apply partitioning best practices across development, staging, and production environments.

Configuring Postgres vacuum and analyze schedules involves tuning settings to update outdated statistics and improve reliability. This Skill offers step-by-step guidance and real-world SQL examples to optimize vacuum and analyze routines for better throughput.

Tuning Supabase RLS policies requires applying deterministic rules to ensure security does not degrade query speed. This Skill provides concrete SQL examples and best practices to structure RLS policies efficiently across different environments.

Yes, these Postgres best practices apply across development, staging, and production environments. The Skill delivers performance monitoring scenarios and configuration tuning steps tailored to each environment to ensure scalable database design and reliable query optimization.

High latency and low throughput in Postgres often stem from poorly designed schemas, suboptimal indexing, and under-optimized configuration. This Skill identifies these specific performance bottlenecks and applies structured best practices to fix them.