SubhanHakverdiyev

SubhanHakverdiyev / OptimizeQL

Public

OptimizeQL — AI-powered SQL query optimizer

21
1
100% credibility
Found Feb 25, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

OptimizeQL is a web application that connects to PostgreSQL or MySQL databases, runs query execution plans, and uses AI to suggest indexes, rewrites, and optimizations.

How It Works

1
🔍 Discover OptimizeQL

You find this helpful tool on GitHub that promises to make your slow SQL queries faster using smart AI suggestions.

2
🚀 Start the app

With one simple command using Docker, your personal SQL assistant launches on your computer and opens in your web browser.

3
🔌 Link your database

In the friendly web interface, you add details about your PostgreSQL or MySQL database so it can peek inside safely.

4
🤖 Pick an AI helper

You connect a smart AI service by entering its access details, keeping everything private and secure.

5
✨ Analyze your query

Paste your SQL query into the editor, choose your database if you want live insights, and click Analyze to get magic suggestions.

6
💡 Review suggestions

You see clear ideas like new indexes to add, better ways to write the query, or tweaks to make it fly.

✅ Queries speed up

Your database runs faster, you save time, and feel like a SQL wizard with less hassle.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 19 to 21 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is OptimizeQL?

OptimizeQL is an AI-powered SQL query optimizer in Python with a Dockerized FastAPI backend and Next.js frontend. Paste any SQL query—it optionally connects to PostgreSQL or MySQL, runs EXPLAIN ANALYZE, pulls schema stats, and feeds it to LLMs for suggestions like CREATE INDEX statements, rewrites, materialized views, and config tweaks ranked by impact. No live DB? It still delivers static analysis plus query history for reuse.

Why is it gaining traction?

One docker compose up launches the full stack with Swagger docs, no env tweaks needed—encryption auto-handles API keys and DB creds. Supports 9 LLM providers (Anthropic, OpenAI, Gemini, OpenRouter, etc.) via UI, plus query comparison to verify rewrites match original results. Actionable output with plan node ties and root causes beats generic profilers.

Who should use this?

Backend devs chasing prod query slowdowns, DBAs prototyping indexes without pgBadger deep dives, data engineers tuning analytics pipelines. Perfect for teams on Postgres/MySQL wanting quick LLM-boosted insights over manual EXPLAIN dissection.

Verdict

Early but solid at 18 stars and 1.0% credibility—83 tests cover core flows, docs detail Docker/local setup and API. Spin it up for real SQL optimizer value; contribute if you need more dialects.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.