Scale and enable data engineering teams to automate complex pipelines with sophisticated data transformations.
For organizations and teams that require advanced features and unlimited potential.
Pachyderm is available in two editions, Community and Enterprise. The table below highlights the key differences between the editions
 | Community Edition | Enterprise Edition |
|---|---|---|
| Console | ||
| Notebook Support | ||
| Immutable Data Lineage | ||
| Native Data Version Control | ||
| Deduplication | ||
| Data Driven Pipelines | 16 | Unlimited |
| Parallel Processing (Parallel Workers) | 8 | Unlimited |
| Role Based Access Controls (RBAC) | - | |
| Pluggable Auth – Login with your IdP | - | |
| Enterprise Support | - | Download Community | Contact Sales |
Offering mission-critical reproducibility across BioTech, Pharma, Genomics, Healthcare, and Life Sciences.
The foundation of any production-scale ML platform for data processing and orchestration.
A breast cancer detection system based on radiology scans scaled and visualized using Pachyderm.
A notebook showing how to use the JupyterLab Pachyderm Mount Extension to mount Pachyderm data repositories into your Notebook environment.
This Notebook provides an introduction to Pachyderm, using the pachctl command line utility to illustrate the basics of data repositories and pipelines.
Learn how companies around the world are using Pachyderm to automate complex pipelines at scale.
Pachyderm helps us convert our existing data science pipelines from manually managed scripts to scalable, repeatable end-to-end workflows; enabling us to focus more on developing transformative technology to drive agriculture forward instead of wrangling infrastructure.
View Case Study Pachyderm helps us convert our existing data science pipelines from manually managed scripts to scalable, repeatable end-to-end workflows; enabling us to focus more on developing transformative technology to drive agriculture forward instead of wrangling infrastructure.
View Case Study Pachyderm helps us convert our existing data science pipelines from manually managed scripts to scalable, repeatable end-to-end workflows; enabling us to focus more on developing transformative technology to drive agriculture forward instead of wrangling infrastructure.
View Case Study
