CSV is universal but inefficient: it's plain text, every value is a string, and large files are slow to scan. Apache Parquet stores the same data column-by-column, compressed and strongly typed — typically a fraction of the size and far faster for analytics. This page converts a CSV into Parquet in your browser, with nothing uploaded.
Why convert CSV to Parquet?
- Much smaller files. Columnar storage plus compression often shrinks a CSV by 5× or more.
- Faster queries. Tools like Spark, pandas, and Polars read Parquet far quicker, and can skip columns they don't need.
- Real types. Numbers stay numbers and dates stay dates — no re-parsing strings every time you load the file.
- A better archive format for data you'll query again later.
Types are detected automatically
When the CSV loads, the engine samples it to infer each column's type — integers, decimals, booleans, dates, and timestamps — so the resulting Parquet is properly typed rather than all-text. You can review the inferred schema in the column headers before exporting, and use SQL to cast or clean a column if you want to override the guess.
The Parquet file is written out compressed and columnar, with the schema baked in, so it's ready for analytics tools straight away.
Private by design. Your file is read and converted locally — in your browser on the web, or on-device in the macOS app. The contents are never uploaded to us or to any third party. Read our privacy policy.
How large a file can I convert? The free web viewer exports up to 1,000 rows — plenty to try it out or convert small files. Pro raises that to 100,000 rows in the browser, and the macOS app exports files of any size, from a few rows to hundreds of millions, with the same local-only privacy.
