Apache Arrow is a universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics. It contains a set of technologies that enable data systems to efficiently store, process, and move data. The reference Arrow libraries contain many 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 Readers and writers for various widely-used file formats (such as Parquet, CSV) The official Arrow libraries in this repository are in different stages of implementing the Arrow format and related features. See our current feature matrix on git main. If you are using AI coding tools, please review our [AI-generated code guidance][7]. We use [runs-on][5] for managing the project self-hosted runners. We use [AWS][6] for some of the required infrastructure for the project.
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).