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PARQUET to CSV converter, without the upload.

Turn a Parquet file into a CSV you can open in Excel. It is converted in your browser, so the file never leaves your device.

Drop PARQUET files here

or choose from your computer paste with Ctrl V

Ready · other file types work too0 bytes uploaded, ever

Convert to

How to convert PARQUET to CSV

  1. Add your PARQUET datasets

    Drop PARQUET files onto the box above, or click it to choose them. ToAny reads the file's contents to detect the type, so a wrong extension does not matter.

  2. CSV is already chosen

    Press Convert. There is nothing else to set. The work happens in this tab.

  3. Download

    Save the CSV, or download everything as one ZIP if you converted several files.

Why ToAny

  • Private by construction

    The PARQUET to CSV converter is part of this page and runs inside your browser. Your datasets are never sent to ToAny or to anyone else.

  • No upload, no queue

    Nothing has to travel to a server and back, so the conversion starts the moment you press Convert, even on a slow connection.

  • Free, without an account

    No sign-up, no email address and no watermark. Add several files and download them together as a ZIP.

PARQUET to CSV: what to expect

Parquet is a columnar format used by data lakes, Spark and analytics tools. Excel and most spreadsheets cannot open it, but they open CSV. The column names and values come across as text; Parquet's column types and its compression do not.

Column types are read from the file and nested columns stay nested. An encrypted Parquet file is refused, and so is one too large to hold in a browser tab (about 40 million cells).

PARQUET vs CSV

PARQUET

Apache Parquet table

Parquet stores a table column by column, with the type of every column recorded in the file and each column compressed on its own. That makes it small and quick to scan for analysis, which is why data lakes and warehouses use it. It cannot be read in a text editor or a spreadsheet.

Opens in pandas, Spark, DuckDB, BigQuery, Snowflake and other analytics tools; not Excel

PARQUET converter
CSV

CSV spreadsheet

CSV is a table written as text: one row per line, values separated by commas. Every spreadsheet and database can import and export it, but it holds one sheet only and no formatting, formulas or data types.

Opens in Excel, Google Sheets, Numbers, databases and any text editor

CSV converter
PARQUET compared with CSV
PARQUETApache Parquet tableCSVCSV spreadsheet
Stands forApache ParquetComma-Separated Values
TypeColumnar data filePlain-text table
CompressionLossless (per column: Snappy, Zstandard, gzip and others)None
Introduced2013, by Twitter and Cloudera, now the Apache Software FoundationThe 1970s, by no single author (described in RFC 4180)
Opens inpandas, Spark, DuckDB, BigQuery, Snowflake and other analytics tools; not ExcelExcel, Google Sheets, Numbers, databases and any text editor
Best forLarge analytical datasetsMoving tabular data between systems
File extension.parquet.csv

Questions

Are my datasets uploaded anywhere?

No. The PARQUET to CSV conversion runs inside your browser, on your own phone or computer. The file is not sent to ToAny or to anyone else.

Is anything lost when converting PARQUET to CSV?

The values are kept. Anything CSV has no way to express, such as formatting, formulas or nesting, is simplified or left out.

Can I convert several PARQUET files at once?

Yes. Add as many as you like, convert them together and download each result or all of them as one ZIP.

How do I convert PARQUET to CSV on Windows, Mac, iPhone or Android?

The steps are the same everywhere because ToAny runs in the web browser: open this page in a current version of Chrome, Edge, Safari or Firefox, add the PARQUET file, press Convert and save the CSV. There is nothing to install.

Is there a file size limit?

Yes. Binary data files up to 150 MB are accepted; a larger file is refused with a message. Beyond that the limit is your device's memory, since nothing is uploaded; a computer copes with large files better than a phone.