Do I need to provide a schema?

No. If you don't paste a schema, the tool uses common-sense table and column names (users, orders, created_at) and notes its assumptions in the output. Providing a schema makes the output precise and runnable against your database without column-name fixes.

Which dialects are supported?

PostgreSQL (default), MySQL/MariaDB, SQLite, SQL Server (T-SQL), and BigQuery. Dialect-specific syntax (LIMIT vs TOP, BigQuery's DATE_TRUNC, Postgres arrays) is respected.

Is the output safe to run directly?

Review before running. Always. The tool writes SELECT queries reliably; destructive queries (UPDATE, DELETE, DROP) will run but should be reviewed. For production, run it as a read-only user against a dev copy first.

How is this different from ChatGPT with my schema?

Same result, no signup and no lose-the-output-when-tab-closes. If you have a complex warehouse schema, ChatGPT's larger context window may work better. For typical 1-5 table queries, this tool is faster and simpler.

What's the input limit?

600 characters for the request, 3,000 characters for the optional schema. Keep the request tight; paste only the tables you need.

Natural Language to SQL

Type 'top 10 countries by active subscribers this year' and get a working SQL query. Supports PostgreSQL, MySQL, SQLite, SQL Server, and BigQuery. Paste your CREATE TABLE schema (optional) for precise column names — skip it for generic SQL. Returns the query plus 1-2 sentences of assumptions made. Powered by Amazon Nova Micro. Free, daily-capped.

Describe what you want in plain English. Add your schema for precise output, or skip it for generic SQL.

Dialect:

What do you want? (plain English)0 / 600

Schema (optional — paste CREATE TABLE or describe tables)0 / 3,000

Tips

• Include schema for precise column names and types
• Be specific: "top 10" not "best", "last 30 days" not "recent"
• Mention the filter column for time ranges (created_at vs updated_at)
• Pair with SQL Formatter to pretty-print the output
• Pair with SQL-to-Natural-Language to explain existing queries

Next useful step

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Frequently Asked Questions

Do I need to provide a schema?: No. If you don't paste a schema, the tool uses common-sense table and column names (users, orders, created_at) and notes its assumptions in the output. Providing a schema makes the output precise and runnable against your database without column-name fixes.
Which dialects are supported?: PostgreSQL (default), MySQL/MariaDB, SQLite, SQL Server (T-SQL), and BigQuery. Dialect-specific syntax (LIMIT vs TOP, BigQuery's DATE_TRUNC, Postgres arrays) is respected.
Is the output safe to run directly?: Review before running. Always. The tool writes SELECT queries reliably; destructive queries (UPDATE, DELETE, DROP) will run but should be reviewed. For production, run it as a read-only user against a dev copy first.
How is this different from ChatGPT with my schema?: Same result, no signup and no lose-the-output-when-tab-closes. If you have a complex warehouse schema, ChatGPT's larger context window may work better. For typical 1-5 table queries, this tool is faster and simpler.
What's the input limit?: 600 characters for the request, 3,000 characters for the optional schema. Keep the request tight; paste only the tables you need.

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Describe what you want in plain English, get a SQL query back. Optional schema input for precise column names. 5 dialects supported. Free, no login. This AI-backed tool sends your input to MarkdownMe's capped Amazon Bedrock endpoint to generate the result. No account is required. MarkdownMe provides free, fast, and reliable Markdown tools for developers, writers, and anyone who works with Markdown.