AutoTune-SQL is an AI and Machine Learning powered SQL optimization platform that helps developers analyze, optimize, and evaluate database queries before deployment.
The platform combines Large Language Models, Machine Learning-based risk assessment, query performance analysis, and an integrated SQL learning academy to create a complete environment for both query optimization and developer education.
🌐 Click the image below to visit the live AutoTune-SQL website and experience the platform firsthand.
AutoTune-SQL is designed to answer three critical questions:
- Is this query correct?
- Is this query efficient?
- Is this query safe for production?
Modern applications often suffer from slow database performance due to inefficient SQL queries, missing indexes, expensive joins, poor filtering strategies, and scalability issues.
AutoTune-SQL addresses these challenges through:
- AI-assisted query optimization
- Machine Learning risk prediction
- Query performance analysis
- Intelligent SQL recommendations
- Interactive SQL education and certification
The platform enables developers to improve database performance while simultaneously learning the concepts behind optimization decisions.
AutoTune-SQL leverages Large Language Models to analyze SQL queries and generate optimized alternatives.
Capabilities include:
- Query rewriting
- Optimization suggestions
- Readability improvements
- Best-practice recommendations
- Production-grade SQL guidance
Custom ML models evaluate queries and estimate potential performance risks.
The system can identify:
- Expensive scans
- Poor filtering strategies
- High-cost joins
- Missing optimization opportunities
- Potential scalability concerns
Developers receive detailed analysis including:
- Performance diagnostics
- Query structure evaluation
- Optimization insights
- Execution recommendations
- Risk classification
- PostgreSQL integration
- Persistent database connections
- Connection profile management
- Secure credential storage
The integrated academy provides structured learning through:
- Progressive SQL modules
- Topic-focused lessons
- Interactive exercises
- Practical query labs
- Knowledge assessments
- Progress tracking
- Certification system
Upon successful completion of the academy:
- Progress is validated
- Assessments are evaluated
- Certificates are generated
- Completion records are stored and verified
- React
- TypeScript
- Vite
- Tailwind CSS
- Node.js
- Express.js
- Prisma ORM
- Redis
- PostgreSQL
- Groq API
- Llama 3.3
- Prompt Engineering
- AI Query Analysis Pipeline
- Custom Risk Prediction Models
- Query Classification
- Performance Risk Scoring
- Optimization Recommendation Engine
AutoTune-SQL follows a service-oriented architecture where:
- Users submit SQL queries.
- Queries are analyzed by the optimization engine.
- Machine Learning models evaluate risk levels.
- AI services generate optimization recommendations.
- Results are presented through an interactive dashboard.
- Users can learn underlying concepts through the SQL Academy.
This creates a feedback loop between optimization, learning, and performance improvement.
cd backend
npm install
npx prisma generate
npx prisma migrate dev
npm run devcd frontend
npm install
npm run devPORT=
DATABASE_URL=
REDIS_URL=
JWT_SECRET=
GROQ_API_KEY=
GITHUB_CLIENT_ID=
GITHUB_CLIENT_SECRET=
GITHUB_CALLBACK_URL=Abeer Pathela
GitHub: https://github.com/abeerpathela
LinkedIn: https://www.linkedin.com/in/abeerpathela
AutoTune-SQL combines Artificial Intelligence, Machine Learning, and database engineering to help developers write faster, safer, and more efficient SQL.