Parquet Inspector
Inspect Parquet metadata, row groups, column statistics, and encodings without uploading files to a cloud viewer. DataEngUtils opens Parquet locally so you can debug schema drift, missing statistics, and surprisingly large row groups before a pipeline incident becomes a pager. Data engineers use it when a job suddenly doubles storage, when a partner changes a nested field, or when you need to confirm compression and sort order before approving a release. Everything stays on disk — ideal for regulated datasets and production extracts you cannot paste into a website.
Try it free
Available in the desktop app
Parquet Inspector processes local files with Polars in Rust. Multi-gigabyte Parquet and CSV workflows require the native macOS app — nothing is uploaded to the cloud.
SELECT
order_id,
customer_id,
created_at
FROM analytics.fct_orders
WHERE created_at >='2026-01-01'
How it works
1. Open a Parquet file
Drag a file into Parquet Inspector to read footer metadata instantly.
2. Explore schema and row groups
Browse columns, types, null counts, and row group sizes in a native UI.
3. Share findings offline
Copy details into tickets or docs without exposing the underlying rows to the web.
Why not use an online tool?
Online inspectors tools require uploading your Parquet and CSV files to a third-party server. For production work, that is a security and compliance risk. DataEngUtils runs locally — same convenience, none of the exposure.