QueryTuner
QueryTuner is an AI-powered SQL query diagnostics tool that analyzes SQL queries across five major database dialects: PostgreSQL, MySQL, Oracle, SQL Server, and SQLite. It combines a heuristic engine with large language model (LLM) based rewrites to provide consultant-grade performance analysis without requiring a live database connection. Users can paste a SQL query and optionally include an EXPLAIN plan and schema DDL for more accurate, schema-verified recommendations. The tool generates a prioritized list of findings, marking performance issues by severity, and offers copy-pasteable rewritten SQL that optimizes the query. It also produces a security risk report, identifying potential vulnerabilities such as SQL injection patterns. Each analysis can be shared via a permanent URL, enabling collaboration among team members. Additionally, QueryTuner provides an API endpoint (/analyze) for programmatic access, allowing integration into development workflows or CI/CD pipelines. QueryTuner is offered as a paid service, with a free tier possibly available for limited use (though pricing is not detailed on the homepage). The platform supports AI insights through external providers like Hugging Face or OpenAI; however, using OpenAI requires an API key and may not be enabled by default. The project's source code is available on GitHub under an MIT license, indicating an open-source component, though the hosted service itself is commercial. Overall, QueryTuner targets developers who write SQL but are not database administrators, aiming to bridge the gap between SQL proficiency and deep database performance expertise. It is currently at version 0.2.0, suggesting an early-stage product with active development.
- Category
- Database
- Pricing
- Paid
Problem solved
QueryTuner solves the problem of diagnosing and optimizing SQL query performance and security without requiring a live database connection or extensive DBA knowledge. It provides actionable insights, rewrites, and recommendations for developers who need to improve query efficiency but lack specialized database tuning skills.
Use cases
- Analyze slow SQL queries to identify performance bottlenecks and get optimized rewrites.
- Check SQL queries for security risks such as injection vulnerabilities before deployment.
- Generate index recommendations by optionally providing schema DDL.
- Use the /analyze API to integrate SQL analysis into automated testing or CI/CD pipelines.
- Share analysis reports with team members via permanent URLs for collaborative review.
- Support multiple SQL dialects when working with heterogeneous database environments.
Audience
- Developers
- Data Scientists
- ML Engineers
Pros
- Supports five major SQL dialects: PostgreSQL, MySQL, Oracle, SQL Server, and SQLite.
- Provides prioritized findings, rewritten SQL, and security reports in one tool.
- No database connection required; analysis is based on pasted query and optional metadata.
- Offers a /analyze API endpoint for programmatic integration.
- Open-source codebase (MIT license) allows self-hosting or customization.
Cons
- Paid service may limit adoption for individual developers or small teams.
- Early-stage product (v0.2.0) with potentially limited features and stability.
- AI insights require an external AI provider, which may incur additional costs or setup.
- Only five SQL dialects supported; other databases are not covered.
Official website: https://querytuner.com/
Canonical LambdaBase page: https://www.lambdabase.com/tools/querytuner