Vendor Name | Databricks Feature Store |
History | Created by Databricks |
Stand-alone vs. Platform | Part of a broader MLOps platform |
Delivery Model | Fully-Managed Cloud Service |
Clouds Supported | AWS, GCP, Azure |
Pricing Model | Consumption Pricing |
Service Level Guarantees | Uptime |
Support | 24 x 7 support & response time guarantees |
Feature Definitions | Declarative framework for defining features (incl. transformations and materialization) Feature ingestion jobs managed in notebooks Feature definitions are managed with Delta as a backing layer and a metadata managed service for schema enforcement. |
Automated Transforms | Automated pipeline orchestration Managed Batch Streaming and Real-Time Transformations Automated backfill of historical data Pipeline visualization |
Feature Ingestion | Spark (for batch feature ingestion) Pandas (for batch feature ingestion) SQL (for batch ingestion) Spark Streaming (for streaming feature ingestion) |
Storage and Feature Processing Infrastructure | Online currently can be pushed asynchronously to Aurora, RDS MySQL, Azure DB for MySQL, and Azure SQL DB. GCP online sync is still WIP. |
Feature Sharing and Discovery | Web UI Searchable feature catalog with metadata Feature discovery including transformations, data lineage, and values Feature versioning and dependency management |
Training Dataset Generation | Dataset generated from offline storage using Python SDK Integrated with MLflow artifacts to automate retraining feature fetch when linked as a feature store definition |
Online Serving | Allows sync for pushing feature data to online stores (RDS, Azure SQL, etc.) |
Monitoring and Alerting | Data quality monitoring |
Security and Data Governance | Data remains in end-user's cloud account ACL, SSO, RBAC |
Integrations | Batch: Delta (defined in Hive metastore) Streaming ingest through Spark from Kafka, Kinesis, EventHubs. |
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Vendor |
Demo link |
History |
Stand-alone vs. Platform |
Delivery Model |
Clouds Supported |
Pricing Model |
Service Level Guarantees |
Support |
Feature Definitions |
Automated Transforms |
Feature Ingestion |
Storage and Feature Processing Infrastructure |
Feature Sharing and Discovery |
Training Dataset Generation |
Online Serving |
Monitoring and Alerting |
Security and Data Governance |
Integrations |