Tecton Feature Store
Commercial Information
| Vendor Name | Tecton Feature Store |
| History | 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 |
| Support | 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) SSO Data encryption at rest and in flight |
| Integrations | Batch data: S3, Hive/Glue, Redshift, Snowflake Streaming data: Kafka, Kinesis |
Tecton Feature Store FAQ
What is Tecton feature store?
Tecton is a feature store founded by the creators of the Uber Michalangelo platform. It is a stand-alone platform that integrates with other 3rd party MLOps tools.
What is the difference between online and offline materialization in Tecton?
Offline materialization corresponds to calculating and storing historical values of features and is used to speed up the computation of features when generating training data or doing batch inference. Online materialization involves persisting features to a fast storage solution (like Redis or DynamoDB), where they can be retrieved for real-time inference.
What kind of alerting does the Tecton Feature Store have?
Tecton will send users alerts via email for common issues with feature pipelines. Some of these issues include failed jobs, high serving latency, or lower than expected feature freshness.
Who is the Tecton Feature Store for?
Data scientists, data engineers, and machine learning engineers who need to serve complex/precomputed features to real time models, often with very recent freshness. For Tecton in particular, it is for those users looking to have a hosted and managed ready to use platform so developers can focus on building and deploying features and really accelerating the deployment of ML models rather than having to focus on ML infrastructure.
What data sources does the Tecton Feature Store work with
s3/redshift/snowflake/kafka/kinesis
Is the Tecton Feature Store a managed version of Feast?
No. The codebases are separate. However, Tecton fully believes in the Feast Feature Store project and is the main contributor.
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Commercial Information
| Vendor |
| Demo link |
| History |
| Stand-alone vs. Platform |
| Delivery Model |
| Clouds Supported |
| Pricing Model |
| Service Level Guarantees |
| Support |
Feature Store Capabilities
| 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 |