Databricks Feature Store

Input—per 1M tokens

Output—per 1M tokens

Context—tokens

WeightsClosed

About

Databricks Feature Store is ranked #8 of 17 in feature store software on Inferse. It runs on API, Web. A free trial is offered.

Compared on feature store software

Online store: Yesdocs.databricks.com
Offline store: Yesdocs.databricks.com
Point-in-time joins: Yesdocs.databricks.com
Feature monitoring: Yesdocs.databricks.com
Deployment model: clouddocs.databricks.com
Serving modes: bothdocs.databricks.com

Facts

Purpose: Databricks Feature Store is a central registry for the features used in AI and ML models.docs.databricks.com · 30 Sept 2026
Governance and discovery: Registering features and models in Unity Catalog provides governance, lineage, point-in-time joins, and cross-workspace feature sharing and discovery.docs.databricks.com · 30 Sept 2026
Feature authoring: Features can be authored as declarative Feature Views managed through Databricks pipelines or as feature tables populated by writing values to Delta tables.docs.databricks.com · 30 Sept 2026
Feature Views status: Feature Views and their feature materialization capability are in Public Preview.docs.databricks.com · 30 Sept 2026
Model training and inference: Models trained with Feature Store features automatically track feature lineage and look up the latest feature values at inference time.docs.databricks.com · 30 Sept 2026
Training and serving consistency: Databricks says using the same feature computations at inference as during training eliminates training/serving skew.docs.databricks.com · 30 Sept 2026
Real-time serving: Feature serving endpoints and online stores support serving features for real-time applications, with the main overview describing endpoints as providing millisecond latency.docs.databricks.com · 30 Sept 2026
Integrations: Supported third-party online stores include Amazon DynamoDB, Amazon Aurora (MySQL-compatible), and Amazon RDS MySQL, with availability differing by Feature Store mode.docs.databricks.com · 30 Sept 2026
Python client: The Feature Engineering Python client is distributed as databricks-feature-engineering on PyPI and is pre-installed in Databricks Runtime 13.3 LTS ML and above.docs.databricks.com · 30 Sept 2026
Client limitation: Feature Engineering and Feature Store APIs cannot be called from local or other non-Databricks environments, although local IDE development and unit testing are supported.docs.databricks.com · 30 Sept 2026
Workspace requirement: The current Databricks Feature Store requires a workspace enabled for Unity Catalog.docs.databricks.com · 30 Sept 2026
Security and access: Access to Unity Catalog feature tables is managed through Unity Catalog access controls.docs.databricks.com · 30 Sept 2026
Pricing model: Feature Store is billed at cost for underlying serverless compute, online store, and serving infrastructure, with no premium on top.docs.databricks.com · 30 Sept 2026
Pricing components: Materialization uses serverless compute, feature serving endpoints use the Model Serving SKU, and online stores use Lakebase compute priced by capacity units and replicas.docs.databricks.com · 30 Sept 2026