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Columnar In-Memory Data Formats

Ranking updated Jun 30, 2026

High-performance open-source libraries and specifications for sharing structured data across analytical processing tools and systems.

Columnar In-Memory Data Formats

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  • apache/arrowapache avatar

    apache/arrow

    16,529View on GitHub↗

    Arrow is a cross-language development platform for in-memory data. It provides a standardized, language-independent columnar memory format designed to accelerate analytical operations and improve memory efficiency on modern computing hardware. By utilizing a schema-driven approach, the framework enables the efficient organization of both flat and nested data structures. The project functions as an analytical data processing engine that facilitates high-performance computation directly on memory-resident datasets. It distinguishes itself through a zero-copy architecture, which allows multiple

    Apache Arrow is the canonical open‑source columnar in‑memory format that provides a standardized, language‑agnostic columnar layout with zero‑copy sharing and wide multi‑language support, exactly matching the need for efficient data interchange across tools and languages.

    C++Columnar FormatsIn-Process AnalyticsLanguage Interoperability
    View on GitHub↗16,529
  • wesm/featherwesm avatar

    wesm/feather

    2,757View on GitHub↗

    Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow

    Feather is a columnar binary data format built on Apache Arrow, purpose-built for fast, zero-copy data interchange between Python, R, and other languages, exactly matching the need for an efficient, open-source columnar in-memory format for cross-language sharing.

    JavaScriptData Formats
    View on GitHub↗2,757

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