Query JSON & JSONL Files with SQL!

Paste raw JSON/JSONL text or upload a file to query it natively using standard SQL table naming.




Available Fields (Table: data)

Upload/Paste JSON to discover columns...

Write SQL Query

Output Results

No query executed yet.

About This Tool

This free browser-based tool lets you query JSON and JSONL files using standard SQL syntax — no database setup, no server, no upload required. Paste your data or select a file, and it's instantly registered as a queryable table called data. Run SELECT statements with WHERE clauses, ORDER BY, aggregate functions, and more, directly against your JSON structure. Everything runs client-side in your browser, so your data never leaves your device.

Frequently Asked Questions

Can I query a JSONL (JSON Lines) file with SQL?
Yes. Paste JSONL content (one JSON object per line) directly into the input box, or upload a .jsonl file. The tool automatically detects JSONL format and parses each line as a row.

Do I need to write CREATE TABLE statements first?
No. As soon as you parse your JSON or JSONL data, it's automatically registered as a table named data. You can start writing SELECT queries against it immediately.

Is my JSON data uploaded to a server?
No. All parsing and querying happens locally in your browser using client-side JavaScript. Your data is never sent to a server or stored anywhere outside your own browser session.

What SQL features are supported?
This tool uses AlaSQL, an in-browser SQL engine, which supports standard SELECT statements, WHERE filtering, ORDER BY, GROUP BY, JOINs, and common aggregate functions like COUNT, SUM, and AVG.

Can I export my query results?
Yes. After running a query, click "Download CSV" to save your results as a CSV file you can open in Excel, Google Sheets, or any spreadsheet application.

What if my JSON has nested objects?
If your top-level JSON is an object containing a nested collection of records (rather than a flat array), the tool automatically detects this structure and uses the nested records as your table rows, merging in any top-level fields as shared columns.

Does this work with large files?
Since everything runs in your browser's memory, performance depends on your device and browser. It comfortably handles typical JSON/JSONL files used for configs, logs, exports, and API responses.