Why Add SQL to ParquetReader? 🤔

Until now, ParquetReader let you preview, search, and download Parquet, Avro, ORC, and Feather files with ease.

But many users wanted more: the ability to query their data directly — without spinning up databases or writing scripts.

That’s why we’ve added a powerful new feature: run SQL queries instantly in your browser.

Step 1 — Upload Your File 📤

Head to ParquetReader.com and upload your Parquet, Avro, ORC, or Feather file.

As usual, you’ll see the schema and metadata panel after uploading — row count, columns, and file size.

Step 2 — Open the SQL Query Editor ✍️

Scroll down to the Advanced: Run SQL Query panel.

Here you’ll find a built-in SQL editor (with syntax highlighting) where you can type queries against your file.

For example:

`SELECT id, url FROM dataset WHERE user_total_post >= 5000;`

Step 3 — Use `dataset` as Your Table 🔎

Inside the editor, your uploaded file is always available as the table dataset.

No need to guess table names — just query against dataset.

⚠️ Pagination is automatic: ParquetReader handles LIMIT/OFFSET for you so Next/Previous buttons keep working smoothly.

Step 4 — Handle Errors Gracefully ⚠️

If your query has a typo (for example, wrong column name), ParquetReader will show a clear error message.

This helps you quickly adjust your query without digging through logs or cryptic stack traces.

Step 5 — Reset Anytime 🔄

Want to go back to the normal preview mode?

Just click Reset Query and ParquetReader reloads the default preview of your file.

Why This Matters 🔥

Parquet, Avro, ORC, and Feather are powerful formats, but they’re hard to explore without a database or code.

Now, with ParquetReader’s SQL editor, you can run real queries in seconds — perfect for analysts, data scientists, or engineers who just need answers fast.

Think of it as a lightweight cloud SQL workbench for columnar files.

Start Querying Your Data 🚀

Upload your file to ParquetReader, open the SQL panel, and run your first query today.

It’s free to try — and if you need offline or enterprise access, we support secure deployments too.

Try SQL on your Parquet files now →