Want to use Python to run ML experiments or train models on top of RedShift?

Pachyderm data pipelines integrate natively with RedShift

 

ML Engineers that leverage Python are increasingly being tasked with building models on top of RedShift, but getting RedShift connected to data pipelines can be a highly complex and time-consuming project.

Pachyderm’s ML Pipelines for RedShift let you use all your favorite standard python data processing libraries directly on RedShift data.

We provide out-of-the-box integration, data-driven automation, and petabyte scalability, while still ensuring full reproducibility. Our ML Pipelines for RedShift allow your team to iterate rapidly on RedShift data, and get your ML models to production more quickly and reliably.

Concept diagram of how Pachyderm enables Python users to access data in RedShift

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Pachyderm Enables Your Team to build Python-based Workflows on RedShift Data

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About Pachyderm

Pachyderm provides industry-leading data versioning, pipelines, and lineage that allow data science teams to automate the machine learning lifecycle and optimize their machine learning operations (MLOps).

With investment from Benchmark, Microsoft M12, and others, Pachyderm, Inc. offers a user deployed Pachyderm Enterprise Edition, a hosted SaaS Pachyderm Hub, and an open-source Pachyderm Community Edition.

Pachyderm helps customers get their ML and AI projects to market faster, lower data processing and storage costs, and supports strict data governance requirements through data-driven automation, petabyte scalability, and end-to-end reproducibility.