Apache Arrow vs Apache Parquet: Which Should You Use?
Side-by-side comparison of Apache Arrow and Apache Parquet data formats — features, pros, cons, and conversion options.
Apache Arrow is best for In-memory analytics, inter-process data sharing, and columnar computation. Apache Parquet is best for Big data analytics, data lakes, and columnar query engines.
Quick Verdict
- ✓ Zero-copy reads for maximum performance
- ✓ Language-agnostic in-memory format
- ✓ Tight integration with Pandas and Spark
- ✗ Not a storage format (in-memory only)
- ✓ Columnar storage for extremely fast analytics
- ✓ Excellent compression ratios
- ✓ Schema evolution support
- ✗ Not human readable
Specs Comparison
Side-by-side technical comparison of Apache Arrow and Apache Parquet
| Feature | Apache Arrow | Apache Parquet |
|---|---|---|
| Category | Data | Data |
| Year Introduced | 2016 | 2013 |
| MIME Type | application/vnd.apache.arrow.stream | application/vnd.apache.parquet |
| Extensions | .arrow | .parquet |
| Plain Text | ✗ | ✗ |
| Typed | ✓ | ✓ |
| Nested | ✓ | ✓ |
| Human Readable | ✗ | ✗ |
| Schema Support | ✓ | ✓ |
| Streaming | ✓ | ✗ |
| Binary Efficient | ✓ | ✓ |
Pros & Cons
Apache Arrow
- ✓ Zero-copy reads for maximum performance
- ✓ Language-agnostic in-memory format
- ✓ Tight integration with Pandas and Spark
- ✗ Not a storage format (in-memory only)
- ✗ Large overhead for small datasets
- ✗ Requires Arrow libraries
Apache Parquet
- ✓ Columnar storage for extremely fast analytics
- ✓ Excellent compression ratios
- ✓ Schema evolution support
- ✗ Not human readable
- ✗ Requires specialized tools to inspect
- ✗ Overkill for small datasets
When to Use Each
Choose Apache Arrow when...
- You need files optimized for In-memory analytics, inter-process data sharing, and columnar computation
- Zero-copy reads for maximum performance
- Language-agnostic in-memory format
Choose Apache Parquet when...
- You need files optimized for Big data analytics, data lakes, and columnar query engines
- Columnar storage for extremely fast analytics
- Excellent compression ratios
How to Convert
Convert between Apache Arrow and Apache Parquet for free on ChangeThisFile
Frequently Asked Questions
Apache Arrow is best for In-memory analytics, inter-process data sharing, and columnar computation, while Apache Parquet is best for Big data analytics, data lakes, and columnar query engines. Both are data formats but they differ in compression, compatibility, and intended use cases.
It depends on your use case. Apache Arrow is better for In-memory analytics, inter-process data sharing, and columnar computation. Apache Parquet is better for Big data analytics, data lakes, and columnar query engines. Consider your specific requirements when choosing between them.
Go to the Apache Arrow to Apache Parquet converter on ChangeThisFile. Upload your file and the conversion processes on the server, then auto-deletes. It's free with no signup required.
Yes. ChangeThisFile supports Apache Parquet to Apache Arrow conversion. Upload your file for server-side conversion — files are auto-deleted after processing.
File size varies depending on the content, compression method, and quality settings of each format. In general, lossy formats produce smaller files than lossless ones. Test with your specific files to compare actual sizes.
Yes, Apache Arrow supports streaming, but Apache Parquet does not. This may be important depending on your use case.
Both Apache Arrow and Apache Parquet are supported file formats that are free to use. You can convert between them for free on ChangeThisFile — server-side conversions are free with no signup required.
Apache Arrow is newer — it was introduced in 2016, while Apache Parquet dates back to 2013. Newer formats often offer better compression and features, but older formats tend to have wider compatibility.
Related Comparisons
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