CSV to Parquet Converter – Free Online CSV to Parquet Tool

Upload .csv file
or drag and drop
  1. Click the upload area and choose a .csv file, or drag and drop it into the page.
  2. Wait for the tool to parse the CSV file. Review the first rows in the preview table.
  3. Click "Download Parquet" to save the converted file.

Help

FAQ

Is my CSV file uploaded when converting to Parquet?Show
No. The CSV to Parquet converter runs entirely in your browser. Files are parsed and converted locally with DuckDB-WASM and never sent to any server.
How large can a CSV file be?Show
You can convert reasonably large CSV files, but extremely large datasets are limited by your browser's memory. For multi-gigabyte files, it is safer to use desktop tools or CLI.
What compression is used?Show
The output Parquet file typically uses Snappy or ZSTD compression by default, depending on the DuckDB-WASM configuration.

How to convert CSV to Parquet online

  1. Click the upload area and choose a .csv file, or drag and drop it into the page.
  2. Wait for the tool to parse the CSV file. Review the first rows in the preview table.
  3. Click "Download Parquet" to save the converted file.

Privacy

Full guide

CSV to Parquet Converter transforms your CSV files into Parquet format, a columnar storage format optimized for big data analytics.

Why Convert CSV to Parquet?

  • Smaller file size: Parquet uses columnar compression, often achieving 70-90% size reduction
  • Faster queries: Columnar storage enables efficient column pruning and predicate pushdown
  • Schema preservation: Data types are inferred and preserved in Parquet schema
  • Wide compatibility: Parquet is supported by Apache Spark, Pandas, DuckDB, and many data tools

Usage Example

CSV to Parquet Usage Example

Real-World Cases

Case: Optimize Data Pipeline Storage

Original file: sales_data.csv (500MB, 1 million rows)

Requirement: Reduce storage cost and speed up analytics queries

Steps:

  1. Upload sales_data.csv file
  2. Preview the data to verify correctness
  3. Click "Download Parquet"

Result:

FormatSizeQuery Speed
CSV500MBBaseline
Parquet~80MB5-10x faster

The Parquet file is 6x smaller and queries run significantly faster due to column pruning.

Case: Prepare Data for Apache Spark

Original file: user_events.csv (daily export from legacy system)

Requirement: Load into Spark for batch processing

Steps:

  1. Upload the CSV file
  2. Review the preview table
  3. Download the Parquet file
  4. Upload to S3/HDFS for Spark to read

Result: Spark can read Parquet files much faster than CSV, with automatic schema inference and column pruning.