Ask a Question. Get SQL.
Describe your query in plain English — get an executable SQL statement instantly. Supports MySQL, PostgreSQL, BigQuery, Snowflake & SQLite.
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Frequently Asked Questions
What is Ask2SQL?
Ask2SQL is a free AI-powered SQL query generator that converts natural language questions into executable SQL statements. Type what data you want in plain English — like "find all customers who ordered more than $100 last month" — and get a ready-to-run SQL query for MySQL, PostgreSQL, BigQuery, Snowflake, or SQLite.
How do I convert English to SQL?
Type your data question in plain English, select your database dialect (MySQL, PostgreSQL, BigQuery, Snowflake, or SQLite), and click Generate. The AI produces correct SQL with proper syntax — including dialect-specific features like BigQuery's QUALIFY clause or PostgreSQL's ILIKE operator.
What is schema-aware SQL generation?
Schema-aware generation lets you paste your CREATE TABLE definitions in our Schema mode so the AI generates queries using your exact table and column names. This eliminates guessing and produces ready-to-run SQL without manual fixes.
What SQL dialects are supported?
Ask2SQL supports 5 major SQL dialects: MySQL, PostgreSQL, Google BigQuery, Snowflake, and SQLite. Each generates syntax-specific SQL — for example, MySQL uses LIMIT/OFFSET, BigQuery uses QUALIFY and STRUCT, and PostgreSQL supports ILIKE and array operators.
Can Ask2SQL explain and optimize existing SQL?
Yes. Use our Explain mode to get a plain-English breakdown of any SQL query, or Optimize mode to get performance improvements with indexing suggestions and query restructuring.
Is Ask2SQL free?
Yes! You get 10 free SQL queries per day with no signup required. Upgrade to Pro for unlimited queries, priority processing, and query history starting at $9/month.
How accurate is the generated SQL?
The AI generates syntactically correct SQL for standard queries (SELECT, JOIN, GROUP BY, subqueries, window functions). For complex business logic, we recommend using schema-aware mode with your actual table definitions for maximum accuracy. Always review generated queries before running in production.