Install apache-arrow with Homebrew

Project links

• Homepage
• Repository

Commands and aliases

• parquet-dump-arrow-statistics
• parquet-dump-footer
• parquet-dump-schema
• parquet-reader
• parquet-scan

Project history

The official README describes Arrow as a universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics. Its major components include the columnar format, IPC format, Arrow Flight, ADBC, C++ libraries, bindings, and implementations across languages including Python, R, Ruby, JavaScript, Java, Go, Rust, Julia, Swift, and .NET.

Arrow grew as an Apache Software Foundation data project around the problem of interoperability between analytical systems. Instead of every engine inventing a private in-memory table format, Arrow standardizes buffers, schemas, metadata, and IPC so systems can exchange columnar data efficiently.

The Git tag history records early `apache-arrow-0.1.0` tags and a later `apache-arrow-1.0.0`, followed by regular major and minor releases. The modern repository has also split some language implementations into separate official repositories, such as Arrow Go, Arrow Java, Arrow Rust, Arrow JS, and Arrow ADBC, while keeping the format and C++-anchored reference libraries central.

Adoption history

Arrow's adoption came from becoming infrastructure inside analytics engines, databases, dataframe libraries, and file-format tooling. Its value is not usually a standalone CLI; it is the ability for systems to share columnar data without serializing through slow row-oriented or language-specific structures.

The Homebrew package exposes Parquet and Arrow-related command-line tools such as `parquet-reader`, `parquet-scan`, `parquet-dump-schema`, `parquet-dump-footer`, and `parquet-dump-arrow-statistics`. That reflects a common package-manager role for Arrow: install native libraries plus practical inspection tools for columnar data files.

How it is used

Developers use Arrow through language libraries, the C++ implementation, the Arrow format, Arrow IPC, Arrow Flight RPC, and ADBC. Package users may install it directly for the CLI tools, headers, libraries, or as a dependency of higher-level analytics packages.

Arrow is especially important in build graphs that involve Parquet, dataframe runtimes, query engines, and cross-language data interchange. Its package must balance native-code performance, ABI concerns, many language bindings, and compatibility with file formats such as Parquet and CSV.

Why package nerds care

Apache Arrow is one of the canonical modern data infrastructure packages: a format spec, native library, language ecosystem, and CLI-tool bundle in one project. It is a dependency whose version can affect performance, binary compatibility, and interoperability across many data tools.

For package maintainers, Arrow is interesting because it is not a single executable. It is a multi-language, multi-component substrate whose release affects downstream Python, R, C++, Parquet, and database connectivity ecosystems.

Timeline

• 2016: Early `apache-arrow-0.1.0` tag appears in the official Git repository.
• 2020: `apache-arrow-1.0.0` appears in the official Git repository.
• 2022: `apache-arrow-10.0.0` appears in the official Git repository.
• 2025: `apache-arrow-20.0.0` appears in the official Git repository.

Related projects

• Apache Parquet is a file format commonly used with Arrow tooling.
• Arrow Flight and ADBC are Arrow ecosystem projects for RPC and database connectivity.
• Separate official repositories now maintain several language implementations, including Arrow Go, Arrow Java, Arrow Rust, Arrow JS, Arrow Swift, Arrow Julia, and Arrow ADBC.

Sources

• https://arrow.apache.org/docs
• https://github.com/apache/arrow#readme
• https://github.com/apache/arrow.git tags via `git ls-remote --tags`
• source_facts.executables
• source_facts.package-manager