Text2SQL
Text2SQL is a web-based tool that converts natural language questions into SQL queries, enabling users with limited SQL knowledge to interact with databases directly. Built by Zero Data Labs, it leverages Anthropic's Claude API to generate accurate SQL based on user-provided database schemas, example queries, and sample data. Users simply input their anthropic API key, upload their schema (up to 150 tables), optionally provide sample queries and data, and then ask questions in plain English. The generated SQL can be executed directly against the database. The tool includes query history and session management, allowing users to save and resume work. Privacy is a core design principle: the API key is stored only in browser session memory and automatically deleted when the page is closed. The platform does not save, log, or store the API key. For sensitive data, Text2SQL recommends randomizing sample data using the companion tool Randify before uploading, ensuring that raw sensitive data never leaves the user's control. All processing occurs client-side except the API call to Anthropic. Text2SQL is ideal for teams where non-technical members need to access data without waiting for developer intervention. It reduces the time spent on writing complex joins and navigating unfamiliar schemas. By bridging the gap between natural language and SQL, it accelerates data-driven decision-making across business units. As a free, hosted application, Text2SQL requires users to supply their own Anthropic API key; there is no separate pricing for the tool itself, though API usage incurs standard Anthropic fees. It supports common databases as schemas can be extracted from MySQL, PostgreSQL, SQL Server, and more, following the provided schema extraction guide.
- Category
- Ai Databases
- Pricing
- Unknown
Problem solved
Writing SQL queries is a bottleneck in many organizations: non-technical team members lack the skills to query data directly, and developers waste time on complex joins and unfamiliar database schemas. Text2SQL solves this by enabling anyone to generate accurate SQL from natural language, reducing dependency on SQL expertise and speeding up data retrieval.
Use cases
- Business analysts querying sales data without SQL knowledge
- Developers quickly generating complex joins and subqueries
- Product managers exploring user behavior data
- Marketing teams creating ad-hoc campaign reports
- Data scientists prototyping queries during exploratory analysis
- Educators demonstrating SQL concepts from natural language
Audience
- Developers
- Data Scientists
- Business Users
- Product Managers
- Researchers
Pros
- Intuitive web interface with step-by-step setup
- Strong privacy: API key and data are not stored on servers
- Supports schema upload, example queries, and sample data for context
- Free to use beyond your own Anthropic API costs
- Session saving and loading for repeated use
Cons
- Requires an Anthropic API key and incurs usage fees
- Dependent on Anthropic's model accuracy; may produce incorrect SQL
- No self-hosted option for organizations with strict data residency needs
- Limits on uploaded items (150 tables, 300 sample queries, 3000 data rows)
- Lacks direct database connection; users must run generated SQL manually
Official website: https://text2sql.io/
Canonical LambdaBase page: https://www.lambdabase.com/tools/text2sql