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    backblaze-labs

    backblaze-labs/awesome-ml-data-pipelines

    A curated list of ML data pipeline tools: dataset versioning, labeling, feature stores, workflow orchestration, data loaders, and storage infrastructure for training and inference.

    data-engineering
    machine-learning
    b2-labs
    data-curation
    data-labeling
    data-pipeline
    data-processing
    CC0-1.0
    1 stars
    0 forks
    1 GitHub watchers
    Updated Nov 5, 2026
    View on GitHub

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    SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.

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    Where it stands

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

    The project lists 2 contributors on GitHub.

    Use Cases & Benefits

    • Curates a comprehensive list of open-source tools for building production ML data pipelines covering orchestration, versioning, feature stores, labeling, processing, and storage.
    • Provides a centralized resource that categorizes and links specialized ML pipeline components, simplifying tool discovery and integration for diverse ML workflows.
    • Use for selecting workflow orchestrators like Apache Airflow or Prefect to schedule and manage complex ML data jobs efficiently.
    • Use for finding data versioning and lineage tools such as DVC or Pachyderm to ensure reproducibility and traceability in ML datasets and models.
    • Use for exploring feature stores like Feast or Hopsworks to serve features consistently for both training and real-time inference in ML applications.

    Should you depend on it?

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

    License

    CC0 1.0

    Public-domain style: no conditions on use.

    Community files

    • README: present
    • Contributing guide: 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

    A curated list of open-source frameworks, engines, and platforms for building production ML data pipelines — orchestration, processing, versioning, feature storage, and everything in between.

    Excerpt from the backblaze-labs/awesome-ml-data-pipelines README on GitHub (CC0-1.0 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

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    +0 stars over 90 days across 86 snapshot days.

    Forks

    0+0

    Open issues

    0+0

    Compared with peers in Data Engineering

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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