vs
csv
Parquet vs CSV: which should you use for data?
A clear, practical comparison with a straight answer.
Use CSV for small, human-readable exchanges and anything that must open in a spreadsheet. Use Parquet once data gets large or you query it repeatedly, where columnar storage and compression cut both file size and query time.
CSV is the format everyone can open; Parquet is the format data teams actually run their queries on. They store the same tables but in opposite ways: CSV row by row as text, Parquet column by column as compressed binary.
For a spreadsheet you email a colleague, CSV wins on simplicity. For a dataset you query again and again, Parquet wins on size and speed, often dramatically.
.parquet vs .csv at a glance
| .parquet | .csv | |
|---|---|---|
| Storage layout | Columnar | Row-based |
| File size | Small (compressed) | Large (plain text) |
| Human-readable | No, binary | Yes, plain text |
| Schema and types | Built in | None, everything is text |
| Query speed | Fast, reads only needed columns | Slow, scans every line |
| Best for | Analytics and data lakes | Small exports and spreadsheets |
Frequently asked questions
Is Parquet always smaller than CSV?
Almost always, because it compresses each column and stores types compactly. The saving grows with the size and repetitiveness of the data.
Can I open Parquet in Excel?
Not directly in older Excel. Convert it to CSV first, or use a tool like DuckDB or pandas. CSV remains the format for spreadsheet users.