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 table view?
Just click Reset Query and ParquetReader reloads the default view 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.
Need practical checks? Copy the 18 SQL data validation queries for nulls, duplicate IDs, invalid dates, outliers, and clean exports.
It’s free to try — and if you need offline or enterprise access, we support secure deployments too.