Tecton Enriches Machine Learning Data with Latest Feast Release

Tecton, the enterprise feature store company and primary contributor to Feast, is releasing Feast 0.10, the first feature store that can be deployed locally without dedicated infrastructure.

The new release makes it possible for data scientists to reap the benefits of a functionally complete feature store with no infrastructure overhead or maintenance.

Feast has seen strong adoption to date with more than 1,700 GitHub stars and contributions from Agoda, Cimpress, Farfetch, Google Cloud, Tecton and Zulily.

Feature stores have emerged as a critical component of the infrastructure stack for machine learning (ML). They solve the hardest part of operationalizing ML: building and serving ML data to production. They allow data scientists to build better ML features and deploy these features to production quickly and reliably.

Feast 0.10 is delivered as a Python software development kit (SDK) that can be deployed locally in minutes. Additionally, Feast 0.10 is modular and integrates with existing data stacks, eliminating the burden and requirement of deploying and maintaining dedicated infrastructure.

“We originally open sourced Feast to share our feature store technology and accelerate the deployment of all ML-powered applications. Feast 0.10 is a major milestone towards making feature stores easy to adopt for data teams that are just getting started in their operational ML journey,” said Willem Pienaar, creator and an official committer of Feast and architect at Tecton. 

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