postgres-patterns

PostgreSQL indexing patterns guide when to use B-tree, BRIN, GIN, and partial indices to speed up queries. Selecting the correct index type based on data distribution and query structure significantly reduces execution time and improves overall database performance.

Row-level security (RLS) patterns provide configurations for access control and data isolation. Applying these patterns during schema design ensures secure data separation in multi-tenant applications by enforcing tenant-specific access policies directly at the database layer.

PostgreSQL schema design patterns recommend specific data type choices and normalization strategies to balance performance and maintainability. Choosing appropriate data types minimizes storage overhead and prevents type-conversion bottlenecks during complex queries.

Use partial or composite indexes in PostgreSQL when queries frequently filter on specific column subsets or require non-null constraints. These indexing patterns speed up targeted queries by indexing only the relevant rows, reducing index size and maintenance overhead.

You can apply Supabase best practices to an existing PostgreSQL project by auditing current schemas and queries. Implementing these configuration defaults and patterns on a representative workload allows you to measure improvements and align with best practices.