Databricks Feature Store vs FeatHub

Databricks Feature Store is a central registry for features used in AI and machine-learning models. Registering features and models in Unity Catalog provides governance, lineage, point-in-time joins, and discovery and sharing across workspaces. Teams can create features as declarative Feature Views managed through Databricks pipelines or as feature tables populated in Delta tables; Feature Views and their materialization capability are in Public Preview.

Models trained with Feature Store features track lineage and retrieve the latest feature values at inference. Databricks says reusing training computations at inference avoids training/serving skew. Feature serving endpoints and online stores support real-time applications, with the overview describing millisecond latency. Supported third-party online stores include Amazon DynamoDB, Amazon Aurora (MySQL-compatible) and Amazon RDS MySQL, with availability depending on Feature Store mode. This paid cloud service has a free trial and usage-based monthly billing, with rates varying by product, cloud provider and region. It requires a Unity Catalog-enabled workspace; its APIs cannot be called from local or other non-Databricks environments, though local IDE development and unit testing are supported.

FeatHub has no write-up on Specifiction yet; its figures are above.