Tecton Feature Store - Tecton


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The Tecton Feature Store

Build ML features using batch, streaming, and real-time data. Deploy them to production instantly.

Bringing DevOps to ML Data

The Tecton feature store manages data flows for operational ML applications on your cloud infrastructure. It brings the principles of DevOps to the entire feature lifecycle and allows data scientists to build and deploy new features within hours instead of weeks.


Using the Tecton Feature Store


Connect Data Sources

Tecton connects directly to batch data sources (e.g. Amazon S3, Redshift, Snowflake) and streaming data sources (e.g. Kafka, Amazon Kinesis).


Define Features

Create new features using Python, SQL, and PySpark. Register new features with Tecton.


Continuously Generate Feature Values

Tecton orchestrates the transformation logic to generate both historical backfill values and fresh feature values. The values are stored in offline and online storage.


Serve Features for Training and Inference

Create accurate training datasets with just a few lines of code in your preferred notebook environment. Retrieve fresh feature values from Tecton’s REST/gRPC API to power real-time predictions in production.

Product Capabilities

Tecton is a complete data platform for ML teams to build, deploy, and share ML features.


Combine Batch, Streaming, and Real-Time Data

Use all your enterprise data to build high-quality features. Combine batch data (e.g. Amazon S3, Amazon Redshift, Snowflake), streaming data (e.g. Apache Kafka, Amazon Kinesis), and real-time data. Real-time data is passed to Tecton at the time of the feature request, and Tecton executes on-demand transformation to generate real-time values.

Manage features as code

Define features in Python files that contain the transformation logic and metadata needed to compute features on an ongoing basis. Version-control your features (e.g. in Git) and integrate them with your existing Code Review and CI/CD processes.

Develop with familiar data science tools

Build features using familiar programming languages and libraries including Python, SQL and PySpark. Use Tecton’s Python SDK in your preferred notebook environment to create training datasets.

Generate accurate training data

Create accurate training datasets with just a few lines of code. Use row-level time travel to deliver the right values at the right time, for each individual row.

Real-time Window Aggregation Features

Out of the box, Tecton supports fresh (<1s) time window aggregation features at high scale (>10,000s QPS) and low latency (<10ms). Learn more about how we do it here.

Real-time Window Aggregation


Plan feature changes with confidence

“Am I about to modify a feature used in production? How much will this feature cost to process? Is this new feature a duplicate?” Before applying your changes, Tecton generates a plan that allows you to answer these questions. Test changes in private workspaces before deploying them to your production environment, and integrate seamlessly with your existing CI/CD pipeline.

Automate feature transformations

Tecton orchestrates data pipelines to generate backfills and continuously compute fresh feature values. Alternatively, ingest feature data from pipelines managed outside of Tecton.

Ensure data consistency

Provide a single source of truth for feature data across your organization. Tecton stores historical data in offline storage, and fresh data in online storage for low-latency retrieval. Ensure data consistency over time and eliminate training / serving skew. Reproduce historical data sets with row-level time travel to deliver the right values at the right time, for each individual row.

Serve features online

Retrieve feature values from Tecton’s REST/gRPC API to power real-time predictions in production at high scale. Median serving latencies are ~5ms and can easily scale to 10,000s of requests per second.

Monitor data quality and operational metrics

Monitor features at every step of their lifecycle. Validate ingested data and detect data drift. Monitor operational metrics including serving latencies, serving volumes, and storage consumption.


Search and discover features

Build a unified catalog of features across your organization. Enable teams to search and discover existing features to enable re-use across teams and models. Track detailed information on each feature including data lineage, feature health, and feature value distribution to increase confidence in existing features


Enterprise-grade security

Tecton is deployed in your VPC, so your data never leaves your cloud account. Control access to individual features and data with Role-Based Access Control and ACLs. Integrate with AWS IAM, Okta, or any solution that supports SAML or Oauth.

Built for scale

Based on Uber Michelangelo’s battle-tested architecture blueprint, Tecton is built for scale and can support thousands of models, tens of thousands of features, and millions of predictions per second. You can start small, and Tecton will scale with you.


Integrates with your data infrastructure

Tecton integrates with your data lake, data warehouse, and streaming platform. In addition, Tecton can perform real-time transformations on data that is passed in real-time with the feature request.

Integrates with all MLOps platforms

Tecton integrates with MLOps platforms such as Amazon SageMaker, Kubeflow, and Databricks via its Python SDK. Manage your Tecton environment directly in your preferred notebook environment such as Databricks, SageMaker, and Jupyter notebooks. Create training datasets and serve features in production for models managed by your existing MLOps platform.

Built for the Cloud

Fully-managed service

Let Tecton manage your feature store with guaranteed SLAs and enterprise support. Tecton is built on best-in-class cloud services to maximize resilience and scale.

Choice of deployment models

Tecton can run in your private VPC so that your data never leaves your account. Alternatively, we can host Tecton as a standalone service to get you off the ground within minutes.

Elastic scalability

Tecton optimizes resource utilization and scales dynamically based on your requirements. We scale compute, storage, and serving independently to adjust to your usage patterns.


Tecton is priced on consumption so you only pay for what you use. Start small and scale pricing with your usage.

Learn more about the Tecton Enterprise Feature Store

What is a Feature Store?

Read the blog

Tide Case Study

Read the case study

Tecton Feature Store Overview

Download the paper

Omdia: Up Close with Tecton

Read the report

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