Quick Install - On VM, On-premises or on your own system;
Quick Install - With Azure CLI or GCP CLI;
A feature store is a powerful centralized storage for machine learning features; it allows organizations to repeat, re-use, improve and govern their machine learning model and data within an open ecosystem that can be connected to multiple data sources for ingestion and data science tools for serving. The feature store solves the most essential pieces of the data for ai infrastructure, bridging DataOps and MLOps.
The feature store allows the automation and management of feature engineering and serving at scale for stream and batch data. Hopsworks is the most advanced open source feature store with an end-to-end machine learning platform for development and operation of machine learning models.
Organize work in self-service teams with GDPR-compliant data storage and processing.
Add GPUs to your cluster and users can use them as needed - with quotas.
Start small on a single VM and scale to clusters of 1000s of CPUs/GPUs and PBs of data.
Run Jupyter notebooks as jobs or use PyCharm plugin. Install libraries with, conda/pypi.
Runs on commodity hardware; support for Ubuntu/Debian and Redhat/Centos.
Use Hopsworks to build paid services on it. If, however, you modify the code, you should release it as AGPL-V3.
• Centos/RHEL 7.x or Ubuntu 18.04;
• at least 32GB RAM,
• at least 8 CPUs,
• 100 GB of free hard-disk space,
• outside Internet access (if this server is air-gapped, contact Hopsworks' team for support).