postgres-patterns

When creating a composite PostgreSQL index for equality and range queries, place the equality column first, followed by the range column. This structure allows the index to efficiently filter exact matches before scanning the sorted range.

Designing a PostgreSQL schema for fast performance requires selecting the most appropriate data types and planning your indexing strategy. Applying Supabase best practices ensures efficient table structures and robust database operations.

Partial or covering PostgreSQL indexes should be used instead of standard B-tree indexes when you need to optimize specific query subsets or avoid table lookups. Partial indexes filter rows by conditions, while covering indexes include extra columns.

Row Level Security in a PostgreSQL database restricts data access by attaching security policies directly to tables. These policies evaluate user attributes for each row, ensuring users only see or modify the data they are authorized to access.

Yes, you can optimize slow PostgreSQL queries using Supabase connection pooling best practices. This Skill provides troubleshooting patterns for inefficient SQL, indexing recommendations, and connection pooling setup to resolve performance bottlenecks.

BRIN indexes for PostgreSQL query optimization are limited to naturally ordered data, such as time-series tables. They store block range summaries instead of individual row pointers, making them highly space-efficient but slower for uncorrelated data retrieval.