Featureform
Virtual feature store that turns existing infra into ML feature serving.
Acquired — still operating
acquired by Redis 2026
About
Featureform is an open-source virtual feature store for machine learning. Instead of copying data into a separate system, it defines and serves reusable features on top of existing infrastructure like Snowflake, Spark, and Redis. Data scientists define transformations, features, labels, and training sets in a standardized form with lineage and ownership metadata.
The platform unifies training and inference workflows with point-in-time correctness, low-latency online serving, and data drift detection. In 2026, Featureform was acquired by Redis to power real-time structured data for AI agents within the Redis data platform.
What it can do
- Virtual feature store, no data copying
- Training/inference parity
- Point-in-time correctness
- Data drift detection
- Integrations with Spark, Snowflake, Kafka, Redis
Setup
Deploy via Helm or pip install featureform; register providers from a notebook.
Prerequisites
Existing data infra (warehouse, Redis); Python for the client.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 126; Trending score 72/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.