- Model Deployment
Automate data transformations with data versioning and lineage
Pachyderm offers custom pricing plan
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Pachyderm is a powerful and scalable data platform designed to enable data engineering teams to automate complex pipelines efficiently across diverse data types. It offers parallelized processing of multi-stage, language-agnostic pipelines, coupled with powerful data versioning and lineage tracking. This ... Read More
Yearly plans
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Community
Custom
Console
Notebook Support
Immutable Data Lineage
Native Data Version Control
Deduplication
16 Data-Driven Pipelines
8 Parallel Processing (Parallel Workers)
Enterprise
Custom
Console
Notebook Support
Immutable Data Lineage
Native Data Version Control
Deduplication
Unlimited Data-Driven Pipelines
Unlimited Parallel Processing (Parallel Workers)
Role Based Access Controls (RBAC)
Screenshot of the Pachyderm Pricing Page (Click on the image to visit Pachyderm 's Pricing page)
Disclaimer: Pricing information for Pachyderm is provided by the software vendor or sourced from publicly accessible materials. Final cost negotiations and purchasing must be handled directly with the seller. For the latest information on pricing, visit website. Pricing information was last updated on .
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San Francisco, California
Pachyderm is a powerful and scalable data platform designed to enable data engineering teams to automate complex pipelines efficiently across diverse data types. It offers parallelized processing of multi-stage, language-agnostic pipelines, coupled with powerful data versioning and lineage tracking. This allows organizations to maintain transparency and traceability in their data workflows, ensuring that changes are tracked across the entire pipeline. Pachyderm MLOps integrates with various tools to create a cohesive machine learning lifecycle. The platform serves as a flexible CI/CD engine for data, facilitating the automation of data pipelines from ingestion to production. As a founding member of the AI Infrastructure Alliance, Pachyderm plays a vital role in promoting open, seamless integration across machine learning tech stacks, enhancing collaboration and innovation within the industry.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].
Researched by Rajat Gupta