Rapidly productionize and scale your machine learning lifecycle

  • Automated Data Versioning

    Pachyderm’s Data Versioning gives teams an automated and performant way to keep track of all data changes

    • Utilizes a Git-like structure that enables effective team collaboration through commits, branches and rollbacks
    • Optimized storage framework supports petabytes of structured and unstructured data, while minimizing storage costs
    • File-based versioning provides a complete audit trail for all data and artifacts across pipeline stages, including intermediate results
    • Stored as native objects (not metadata pointers) so that versioning is automated and guaranteed
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    Automated Data Versioning
  • Data-Driven Pipelines

    Pachyderm’s Containerized Pipelines speed data processing while lowering compute costs

    • Kubernetes native approach supports any library or language
    • Autoscale with parallel processing of data without writing additional code
    • Automated pipelines execute whenever new data is committed
    • Incremental processing saves compute by only processing differences and automatically skipping duplicate data
    • Pipeline steps have JSON/YAML defined inputs and outputs that ease debugging
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  • Immutable Data Lineage

    Pachyderm’s data lineage provides an immutable record for all activities and assets in the ML lifecycle:

    • Track every version of your code, models, and data
    • Maintain reproducibility of data and code for compliance
    • Manage relationships between historical data states

    Pachyderm’s Global IDs make it easy for teams to track any result all the way back to its raw input, including all analysis, parameters, code, and intermediate results.

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  • Console

    The Pachyderm Console provides an intuitive visualization of your DAG (directed acyclic graph), and aids with debugging and reproducibility with Global IDs

    • See the overall structure and flow of all your pipelines
    • Ease pipeline and workflow design
    • Facilitate collaboration across teams on shared DAGs
    • Drill into pipelines and job details for easy debugging
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  • Notebooks

    Pachyderm’s JupyterLab Mount Extension provides a point-and-click interface to Pachyderm versioned data

    • Accelerate experimentation with easy and intuitive access to versioned data
    • Mount any Pachyderm data repository locally for convenient access
    • Work with versioned data like it’s on your own file system. No Pachyderm knowledge required
    • Explore data with a built in file browser
    • Collaborate across teams with a single source of truth for your data
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  • Enterprise Administration

    Pachyderm provides robust tools for deploying and administering Pachyderm at scale across different teams in your organization.

    • Helm 3 provides robust and standards-based deployment on any public or private cloud
    • Enterprise Server provides easy centralized licensing and administration of all Pachyderm clusters / workspaces
    • Use any identity provider with Pachyderm’s pluggable authentication
    • Role Based Access Control (RBAC), allows for fine grain control over access to clusters and data
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Request a demo from our account team to see Pachyderm in action!

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