Machine Learning Feature Stores
For a feature store for ML features, the strongest matches are gojek/feast (Feast is a leading open-source feature store that provides), feast-dev/feast (Feast is a purpose-built open-source feature store that directly) and logicalclocks/hopsworks (Hopsworks is a dedicated feature store platform that provides). featureform/featureform and linkedin/feathr round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Open-source platforms for managing, storing, and serving consistent data features for machine learning model training.
Machine Learning Feature Stores
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- gojek/feast
gojek/feast
7,095View on GitHubFeast is a machine learning feature store and MLOps data infrastructure layer. It provides a centralized system for managing and serving features across offline training and online production environments, utilizing an online feature serving layer for low-latency retrieval. The project centers on a feature registry that acts as a central catalog for defining, governing, and discovering feature services. It employs a unified data access layer to decouple feature retrieval from physical storage and includes a point-in-time data generator to create historically accurate training datasets that pr
Feast is a leading open-source feature store that provides a feature registry, low-latency online serving, point-in-time correct joins, and training data generation, making it exactly the kind of system you need for managing ML features across training and inference.
PythonFeature RegistriesStream IngestionTemporal Join Alignment - feast-dev/feast
feast-dev/feast
6,727View on GitHubFeast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
Feast is a purpose-built open-source feature store that directly covers low-latency online serving, point-in-time correct joins, a feature registry, and offline/online store separation, making it an ideal match for your machine learning feature management needs.
PythonFeature RegistriesFeature View CatalogsReal-Time Prediction Serving - logicalclocks/hopsworks
logicalclocks/hopsworks
1,302View on GitHubHopsworks - Data-Intensive AI platform with a Feature Store
Hopsworks is a dedicated feature store platform that provides offline and online stores, point-in-time correct joins, streaming ingestion, and a feature registry, directly matching your need for consistent low-latency feature serving and training data generation.
JavaData Science ToolsDeep Learning FrameworksFeature Stores - featureform/featureform
featureform/featureform
1,979View on GitHubThe Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Featureform is a virtual feature store that layers on top of your existing data infrastructure, providing a unified feature registry, low‑latency online serving, point‑in‑time joins, and training data generation — exactly what this search is asking for.
GoFeature EngineeringFeature StoreFeature Stores - linkedin/feathr
linkedin/feathr
1,929View on GitHubFeathr – A scalable, unified data and AI engineering platform for enterprise
Feathr is a purpose-built feature store that offers low-latency online serving, point-in-time correct joins, training data generation, a feature registry, streaming ingestion, and separate offline/online stores, matching all the required capabilities for ML feature management.
ScalaFeature Store
