AI for SQL Queries — Tools and Techniques
Use AI to generate and optimize SQL queries quickly.
8 articles
Use AI to generate and optimize SQL queries quickly.
Master PostgreSQL in 2026: JSONB for flexible schemas, full-text search, window functions, CTEs, partitioning, connection pooling, explain analyze, and performance optimization techniques.
The query works fine in development with 1,000 rows. In production with 50 million rows it locks up the database for 3 minutes. One missing WHERE clause, one implicit type cast, one function wrapping an indexed column — and PostgreSQL ignores your index entirely.
Master Postgres query optimization using EXPLAIN ANALYZE, covering index types, query rewriting, and plan analysis for production databases.
Build production databases with Drizzle ORM. Learn schema design, migrations, complex queries, transactions, relations, performance optimization with prepared statements, and when to choose Drizzle over Prisma.
You need to export 10 million rows. You paginate with OFFSET, fetching 1,000 rows at a time. The first batch takes 50ms. By batch 5,000 the offset is 5 million rows and each batch takes 30 seconds. The total job takes 6 hours and gets slower as it goes.
Month 1 — queries are fast. Month 6 — users notice slowness. Month 12 — the dashboard times out. The data grew but the indexes didn''t. Finding and adding the right index is often a 10-minute fix that makes queries 1000x faster.
Page 1 loads in 10ms. Page 100 loads in 500ms. Page 1000 loads in 5 seconds. OFFSET pagination makes the database skip rows by reading them all first. Cursor-based pagination fixes this — same performance on page 1 and page 10,000.