GStars
    apache

    apache/datafusion

    #502 this week

    Apache DataFusion SQL Query Engine

    database
    arrow
    big-data
    dataframe
    datafusion
    olap
    Rust
    Apache-2.0
    9.5K stars
    2.6K forks
    9.5K GitHub watchers
    Updated Oct 23, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #502 of 3,103 repositories GStars tracks this week (top 16%).

    The project lists 426 contributors on GitHub.

    Peaked at #47 in the weekly ranking the week of Aug 2, its best in the past year.

    Use Cases & Benefits

    • Provides an extensible SQL query engine written in Rust using Apache Arrow for in-memory data representation.
    • Delivers high-performance, multi-threaded, vectorized query execution with extensive customization and support for multiple data formats.
    • Use for building domain-specific query engines or custom database platforms tailored to unique workloads.
    • Use for integrating fast SQL and DataFrame query capabilities into Rust or Python data analytics applications.
    • Use for developing data pipelines that require efficient processing of CSV, Parquet, JSON, and Avro data sources.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    • No GitHub releases; pin a commit or tag instead of a release.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    DataFusion is an extensible query engine written in Rust that uses Apache Arrow as its in-memory format.

    This crate provides libraries and binaries for developers building fast and feature-rich database and analytic systems, customized for particular workloads. See use cases for examples. The following related subprojects target end users:

    "Out of the box," DataFusion offers SQL and DataFrame APIs, excellent performance, built-in support for CSV, Parquet, JSON, and Avro, extensive customization, and a great community.

    DataFusion features a full query planner, a columnar, streaming, multi-threaded, vectorized execution engine, and partitioned data sources. You can customize DataFusion at almost all points including additional data sources, query languages, functions, custom operators and more. See the Architecture section for more details.

    DataFusion is great for building projects such as domain-specific query engines, new database platforms and data pipelines, query languages and more. It lets you start quickly from a fully working engine, and then customize those features specific to your needs. See the list of known users.

    Excerpt from the apache/datafusion README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Jul 26: +8Jul 27: +2Jul 28: +17Jul 29: +3Jul 30: +7Jul 31: +8Aug 1: +12Aug 2: +5Aug 3: +5Aug 4: +4Aug 5: +3Aug 6: +2Aug 10: +7Aug 11: +6Aug 12: +11Aug 13: +3Aug 14: +5Aug 15: +4Aug 16: +2Aug 17: +4Aug 18: +2Aug 29: +30Aug 30: +8Aug 31: +4Sep 1: +2Sep 2: +6Sep 3: +2Sep 21: +9Sep 22: +3

    +496 stars over 90 days across 36 snapshot days; best day +30 on Aug 29.

    Forks

    2.6K+292

    Open issues

    2.5K+398

    Compared with peers in Database

    Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth

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