Online SQL Tools

Text to SQL Generator

Convert natural language descriptions into SQL queries instantly using AI (Currently, only translation to MySQL is supported.).

Text to SQL Demo
Prompt
Find top 5 paid orders from last month grouped by user, and only keep users with more than 2 orders.
Generated SQL
SELECT u.id, COUNT(*) AS total_count FROM orders o JOIN users u ON o.user_id = u.id WHERE o.status = 'paid' AND o.created_at >= DATE('now', '-30 days') GROUP BY u.id HAVING COUNT(*) > 2 ORDER BY total_count DESC LIMIT 5;

⚠️ Disclaimer

  • This tool generates SQL for reference only. We do not guarantee 100% accuracy.
  • Please review and test generated SQL before using in production environments.
  • We are not responsible for any data loss or damage caused by using generated SQL.
  • Your input data is processed locally in your browser and is not sent to our servers.

Tips for better results:

  • Be specific about table names if you know them (e.g., "from users table").
  • Specify conditions clearly (e.g., "where price is greater than 100").
  • Mention specific columns you want to select (e.g., "select name and email").
  • For aggregation, include keywords like "count", "group by status", or "per user".
  • You can also use "sum / avg / min / max" and "having count > 5" patterns.

Turn Natural Language Into SQL in Seconds

Text to SQL is built for developers, analysts, and learners who want fast first-draft queries. Describe what you need in plain English, click the arrow button, and refine the generated SQL.

It supports practical patterns such as JOIN, GROUP BY, COUNT, SUM/AVG/MIN/MAX, and HAVING conditions. Great for speeding up exploration before production-level tuning.

FAQ

Q: Can I generate JOIN and aggregation queries?+

A: Yes. Prompts containing user/order/product relations, grouping, and counting are supported.

Q: Does it support HAVING like "count > 5"?+

A: Yes. Try prompts like "group by user having count greater than 5".

Q: Should I use generated SQL directly in production?+

A: Treat it as a high-quality draft, then validate against your schema, indexes, and performance needs.

Examples

Prompt

Count paid orders by status in the last month.

Generated SQL

SELECT status, COUNT(*) AS total_count
FROM orders
WHERE status = 'paid'
  AND created_at >= DATE('now', '-30 days')
GROUP BY status
ORDER BY total_count DESC;