supabase-postgres-best-practices

PostgreSQL performance optimization for high-concurrency apps requires applying best practices for connection pooling, indexing, and concurrency control. This skill provides actionable rules with incorrect and correct examples to manage locks and improve query throughput across typical OLTP workloads.

Writing SQL queries for Supabase analytics workloads involves following data access patterns and query optimization rules. This skill encodes production-grade guidance with concrete examples to structure schema designs and queries that efficiently handle large-scale analytical processing.

Configuring Row Level Security and indexes in PostgreSQL requires applying specific schema design and security rules. This skill provides step-by-step guidance for RLS optimization and indexing strategies tailored specifically for Supabase deployments to ensure reliable data protection.

Using partitioning and vacuuming for Postgres query optimization is necessary when managing large datasets and maintaining database health. This skill offers testable rules for vacuum and analyze configurations, alongside partitioning strategies, to maintain performance and reduce costs in production.

This PostgreSQL best practices guidance explicitly applies to multi-tenant architectures through dedicated security and RLS optimization rules. It encodes real-world scenarios spanning multi-tenant security to help you apply structured patterns for reliable and cost-effective data isolation.