AI Potluck
Infrastructure / Storage & Retrieval

Feast

Feast project

Feast is a feature store that keeps one definition of a feature and serves it from two places: an offline store for building training sets with point-in-time correctness, and an online store for low-latency retrieval at inference. Materialization moves values between them, and a registry holds the definitions. Python, Java and Go components ship from the repository.

Verified 2026-08-18 via the GitHub API and the LICENSE body.

Openness

5 high confidence
5.0
license
Apache-2.0(OSI)
source
public
core-gated
ungated

Apache-2.0 license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.

Adoption

3 high confidence
3.0

724,047 PyPI downloads of `feast` in the trailing 30 days, which lands in the 100K-1M band of the software usage scale, level 3.

Capability

3 medium confidence
3.0

Banded on the category feature matrix as single-purpose store or index. Placed two bands below the vespa anchor, on a matrix that bands on how much of the persist-index-retrieve path a product provides itself, at what scale and over how many retrieval modes.

  • https://github.com/feast-dev/feast/blob/master/README.md recorded 2026-08-18

    README still documents an open source feature store serving features from an offline store for training and an online store for inference, with materialization between them and a registry of definitions.

Verified 2026-08-18