db-advisor

To optimize a slow PostgreSQL query, apply indexing strategies like B-tree, GIN, or BRIN indexes based on your query patterns, and use SQL anti-pattern detection queries to identify unindexed foreign keys and table bloat.

The best way to design a PostgreSQL schema for performance is to select optimal data types for IDs, strings, timestamps, and flags, while implementing composite, covering, or partial indexes for efficient data retrieval.

Yes, this database optimization guidance works with Supabase, offering specific best practices for Supabase operations including Row Level Security (RLS) policy implementation and efficient PostgreSQL configurations.

Use partial indexes in PostgreSQL to index only rows meeting specific conditions for smaller index sizes, and use composite indexes when queries filter on multiple columns simultaneously to optimize complex query patterns.

Your PostgreSQL database has slow queries due to unindexed foreign keys, an anti-pattern detectable via specific SQL queries that identify missing indexes and table bloat, which can be resolved by applying appropriate index recommendations.

To configure essential PostgreSQL settings for performance, apply a configuration template that establishes baseline operational parameters, ensuring efficient database operations and query execution across your environment.