OptimizeQL — AI-powered SQL query optimizer
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Updated
Mar 28, 2026 - TypeScript
OptimizeQL — AI-powered SQL query optimizer
Go library and CLI to parse PostgreSQL EXPLAIN (ANALYZE, FORMAT JSON) output and surface actionable performance findings
PostgreSQL queries from basic joins to window functions, recursive CTEs and measured index optimisation. One e-commerce schema, one Docker command, pure SQL.
Read PostgreSQL EXPLAIN plans locally: parse, compute self time and estimation error, flag documented problems, compare plans, and guard them in CI. No database connection, deterministic.
PostgreSQL slow query watcher, tails auto_explain log output and reports actionable findings using pgexplain
Per-endpoint performance & Big O for your API: OpenAPI spec + EXPLAIN ANALYZE on Postgres/MySQL
Turn PostgreSQL EXPLAIN output into human-readable reports and catch query-plan anti-patterns — every finding tells you exactly how to fix it.
PostgreSQL dimensional data warehouse modeling Romanian national economy across 42 administrative divisions.
Benchmark common SQL performance patterns on PostgreSQL: warm-up, median timings and the EXPLAIN ANALYZE behind every result
PostgreSQL query performance tuning with EXPLAIN ANALYZE, BUFFERS, indexes, joins, materialized views, and correctness verification.
Local-first query profiler for PostgreSQL, MySQL, MongoDB and DuckDB: time per operator, instant problem detection, and an AI advisor that measures fixes before recommending them.
PostgreSQL performance playground built with Spring Boot, Angular and Redis to explore EXPLAIN ANALYZE, indexing strategies, query plans and caching.
Evidence-first PostgreSQL plan analysis with deterministic diagnostics, workload regression checks, and grounded AI/RAG
A macOS PostgreSQL client for learning how queries work: visual execution plans, plain-language explanations, and estimated vs actual rows.
CLI wrapper around pev2 for visualizing PostgreSQL EXPLAIN plans with live reload
Load-testing a production Supabase/Postgres schema at 100x scale to find where the cost actually is. Found a 60x fix hiding in an unindexed self-referencing foreign key.
Advanced SQL analytics on 20.6K Spotify/YouTube tracks (PostgreSQL): schema design, data-quality cleaning, 15 queries from aggregation to window functions & CTEs, plus EXPLAIN ANALYZE query optimization with B-tree indexing.
See the SQL your SQLAlchemy 2.0 statements really run, then read the EXPLAIN ANALYZE plan in plain English — seq scans, stale-stats row mismatches, disk sorts, and expensive nested loops annotated with fixes.
Eight realistic PostgreSQL performance problems, the fix for each, and harness-generated EXPLAIN ANALYZE evidence that the fix worked.
Day 05: eight slow PostgreSQL queries, the fix for each, EXPLAIN ANALYZE before and after on 1M orders, and what the indexes cost on writes
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