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Feast

Open-source feature store for machine learning

Overview

Feast is an open-source feature store that helps ML teams manage and serve features for training and inference. It bridges the gap between data engineering and ML, ensuring consistent features across offline training and online serving.

Key Features

  • Feature Registry: Central catalog of features
  • Offline Store: Historical features for training
  • Online Store: Low-latency feature serving
  • Point-in-time Joins: Correct historical feature retrieval
  • Feature Transformation: On-demand feature computation
  • Multiple Backends: Pluggable storage options

Pros

  • 👍 True open-source
  • 👍 Flexible architecture
  • 👍 Good documentation
  • 👍 Active community
  • 👍 Cloud-agnostic

Cons

  • 👎 Requires setup and maintenance
  • 👎 Less polished than commercial options
  • 👎 Some features still maturing
  • 👎 Limited real-time feature support

Best For

ML teams wanting feature store benefits without vendor lock-in. Good starting point for feature management.

Founded: 2019 HQ: Tecton (maintainer)