Clone this repo:
  1. 0cb737f ARROW-6882: [C++] Ensure the DictionaryArray indices has no dictionary data by Joris Van den Bossche · 70 minutes ago master
  2. 9a87443 ARROW-6283: [Rust] [DataFusion] Implement Context::write_csv to write partitioned CSV results by Andy Grove · 4 hours ago
  3. 884d7cd ARROW-4219: [Rust] [Parquet] Initial support for arrow reader. by Renjie Liu · 4 hours ago
  4. 40c9711 ARROW-6857: [C++] Fix DictionaryEncode for zero-chunk ChunkedArray by Antoine Pitrou · 6 hours ago
  5. d7ad509 ARROW-6873: [Python] Remove stale CColumn references by Uwe L. Korn · 10 hours ago

Apache Arrow

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Powering In-Memory Analytics

Apache Arrow is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast.

Major components of the project include:

Arrow is an Apache Software Foundation project. Learn more at

What's in the Arrow libraries?

The reference Arrow libraries contain a number of distinct software components:

  • Columnar vector and table-like containers (similar to data frames) supporting flat or nested types
  • Fast, language agnostic metadata messaging layer (using Google's Flatbuffers library)
  • Reference-counted off-heap buffer memory management, for zero-copy memory sharing and handling memory-mapped files
  • IO interfaces to local and remote filesystems
  • Self-describing binary wire formats (streaming and batch/file-like) for remote procedure calls (RPC) and interprocess communication (IPC)
  • Integration tests for verifying binary compatibility between the implementations (e.g. sending data from Java to C++)
  • Conversions to and from other in-memory data structures

How to Contribute

Please read our latest project contribution guide.

Getting involved

Even if you do not plan to contribute to Apache Arrow itself or Arrow integrations in other projects, we'd be happy to have you involved: