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CSV vs Parquet
CSV is a human-readable text format for exchanging tabular values. Parquet is a columnar binary format built for efficient storage and reading in analytics systems. Choose for data handoff or large-scale analysis.
Which format should you choose?
Use CSV for simple tables shared with spreadsheets and general-purpose tools. Consider Parquet for analytical datasets where columnar reads and compression help.
Good fit for CSV
Tabular-data exchange
- Transferring one simple table between applications
Good fit for Parquet
Store structured tables for analytics
- Large datasets read by selected columns
Basic information
| Field | CSV | Parquet |
|---|---|---|
| Extension | .csv | .parquet |
| MIME type | text/csv | application/vnd.apache.parquet |
| Common uses | Tabular-data exchange | Store structured tables for analytics |
| How to open | When importing into a spreadsheet, set the character encoding and delimiter. Check that leading zeros, date-like values, and long numbers are not automatically converted. | Use a Parquet-aware tool to inspect schema, column types, row counts, and values. |
| Export or convert | Exporting XLSX to CSV normally writes values from only one selected sheet. Keep formulas, formatting, other sheets, and charts separately. | From CSV or other formats, check types, nulls, timestamps, encoding, partitions, and row counts. |
Choose by use case
Transferring one simple table between applications
Tabular-data exchange
CSVLarge datasets read by selected columns
Store structured tables for analytics
ParquetKey point 1
CSV is text-based and easy to inspect, but does not reliably preserve schema and data types.
More on the differencesKey point 2
Parquet stores data in columnar structures and needs compatible libraries or analytics tools.
More on the differencesMore on the differences
Choose CSV for broad, straightforward exchange. Choose Parquet for supported analytical pipelines, then validate schema, types, nulls, timestamps, and data integrity after conversion.
- CSV is convenient for manual inspection and common application interchange.
- Parquet supports column-oriented processing and compression suited to analytical workloads.
- A conversion can change inferred types or values unless the schema and import rules are checked.
Frequently asked questions
Can a spreadsheet open Parquet like CSV?
Not usually without an extension or another supported tool. Parquet is intended for libraries and analytics systems rather than direct text editing.