Introduction

Feast (Feature Store) is a tool for managing and serving machine learning features.

Feast is the bridge between your models and your data

Feast aims to:

• Provide a unified means of managing feature data from a single person to large enterprises.

• Provide scalable and performant access to feature data when training and serving models.

• Provide consistent and point-in-time correct access to feature data.

• Enable discovery, documentation, and insights into your features.

Feast decouples feature engineering from feature usage. Features that are added to Feast become available immediately for training and serving. Models can retrieve the same features used in training from a low latency online store in production.

This means that new ML projects start with a process of feature selection from a catalog instead of having to do feature engineering from scratch.