Commercial Information

Vendor Name



Founded by the creators of Uber's Michelangelo platform

Stand-alone vs. Platform

Stand-alone feature store, integrates with 3rd party MLOps platforms

Delivery Model

Fully-managed cloud service

Clouds Supported

AWS (now), GCP and Azure (roadmap)

Pricing Model

Consumption Pricing

Service Level Guarantees

Uptime, Serving latencies


24 x 7 support & response time guarantees

Feature Store Capabilities

Feature Definitions

Declarative framework for defining features (incl. transformations and materialization)

Feature definitions are backed in git for central version control and CI/CD integration

Automated Transforms

Automated pipeline orchestration

Managed Batch, Streaming and Real-Time Transformations

Automated backfill of historical data

Pipeline visualization

Feature Ingestion

Spark/Pandas batch feature ingestion into offline & online store

Spark Streaming feature ingestion into offline & online store

Storage and Feature Processing Infrastructure

Online storage: DynamoDB

Offline storage: S3

Feature Processing: Spark and Python

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

Row-level time travel

Online Serving

Serving endpoint / API for online data

Monitoring and Alerting

Managed data drift detection (roadmap)

Data quality monitoring (roadmap)

Monitoring of serving latencies and uptime

Security and Data Governance

Data remains in end-user's cloud account

ACL and RBAC (roadmap)


Data encryption at rest and in flight


Batch data: S3, Hive/Glue, Redshift, Snowflake

Streaming data: Kafka, Kinesis