Apache Arrow is a columnar in-memory analytics layer designed to accelerate big data. It houses a set of canonical in-memory representations of flat and hierarchical data along with multiple language-bindings for structure manipulation. It also provides IPC and common algorithm implementations.

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  1. bcec3e1 ARROW-7651: [CI][Crossbow] Nightly macOS wheel builds fail by Krisztián Szűcs · 12 hours ago master
  2. 5d7209a ARROW-7668: [Packaging][RPM] Use Ninja if possible to reduce build time by Sutou Kouhei · 13 hours ago
  3. bcbd289 ARROW-7674: [Dev] Add helpful message for captcha challenge in merge_arrow_pr.py by Brian Hulette · 14 hours ago
  4. 99f247f ARROW-7518: [Python] Use PYARROW_WITH_HDFS when building wheels, conda packages by Krisztián Szűcs · 17 hours ago
  5. a1eb440 ARROW-7659: [Rust] Reduce Rc usage by Gurwinder Singh · 18 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 arrow.apache.org.

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: