Convert CSV files to Apache Parquet format in your browser. Smaller files, faster analytics, columnar storage.
Parquet uses columnar compression that dramatically reduces file size. A 500 MB CSV often becomes 50-100 MB as Parquet.
Columnar storage means query engines read only the columns they need. Queries on Parquet files run orders of magnitude faster than on CSV.
Standard Apache Parquet output compatible with BigQuery, Spark, Athena, Snowflake, Pandas, Polars, DuckDB, and more.
Unlike CSV, Parquet stores column types natively. No more date parsing issues or numbers read as strings.
Skip the pandas and pyarrow setup. Convert CSV to Parquet directly in your browser. No installation, no command line.
Your data never leaves your device. Conversion runs locally using DuckDB WASM. No upload, no server, no tracking.
Drag a .csv file onto the page. Column types are auto-detected.
Clean columns, filter rows, or fix types before converting.
Click Export, choose Parquet, and download your compressed file.
Parquet files are typically 5-10x smaller than CSV due to columnar compression. They also load much faster in analytics tools like BigQuery, Spark, Athena, and DuckDB because engines can read only the columns they need.
Open exploremydata.com/app, drag your CSV file onto the page, and click Export then choose Parquet. The conversion uses DuckDB WASM running directly in your browser. No Python, no command line, no installation.
Yes. ExploreMyData produces standard Apache Parquet files that work with BigQuery, Spark, Athena, Snowflake, Pandas, Polars, DuckDB, and any other tool that reads Parquet.
Parquet files are typically 5-10x smaller than the equivalent CSV. The exact ratio depends on your data. Columns with repeated values compress especially well in Parquet's columnar format.
Smaller files, faster queries, better analytics. No sign-up required.
Convert CSV to Parquet Free