supabase-postgres-best-practices

Optimize Postgres queries on large Supabase tables by applying concrete indexing strategies like composite, partial, and covering indexes. This skill provides tailored rules for btree, gin, and brin index types to accelerate common queries on tables exceeding 100 million rows.

Table partitioning in Supabase Postgres is needed when managing large datasets to ensure scalable schemas and steady performance. This skill provides concrete guidelines for implementing partitioning alongside proper data types and foreign keys to maintain reliability.

The best way to tune autovacuum and VACUUM settings is by applying curated maintenance rules for healthy performance over time. This skill enforces specific VACUUM, ANALYZE, and autovacuum tuning practices to maintain database operations and reliability.

Row Level Security (RLS) impacts Postgres performance by adding query overhead in multi-tenant Supabase apps. This skill enforces concrete guidelines for RLS performance and access controls to ensure scalable and secure schemas without degrading query speed.

Yes, you can use these Postgres optimization rules for databases with over 100 million rows. The skill is specifically designed to apply Supabase-tailored optimization best practices to large tables and multi-tenant data workloads to achieve steady performance.

Supabase Postgres queries may be slow despite indexes due to schema design flaws, outdated statistics, or inefficient RLS policies. This skill diagnoses and fixes performance issues by applying rules for query analysis, VACUUM, ANALYZE, and proper indexing strategies.