Test and Validate Feature Quality with Tecton

December 18, 2023

Tecton ensures the quality of machine learning features in production.

Visualizing Feature Lineage with Tecton Dataflow

December 11, 2023

Tecton is the interface between raw data and production ML models. Sitting at the intersection between data and AI enables Tecton to provide powerful visibility into feature lineage – namely, what raw data ultimately powers which models. Today …

Orchestrating Feature Pipelines: Announcing the Tecton Airflow Provider

October 31, 2023

The Tecton Airflow provider allow feature platform orchestration through the management of Tecton Feature Views and Feature Services in Airflow.

Combining Online Stores for Real-Time Serving

October 10, 2023

Tecton uses Redis or DynamoDB as an online store for production machine learning. This post provides examples that use both databases together

A Closer Look at the Latest Feature Engineering Workflow Improvements in Tecton 0.6

March 31, 2023

Tecton 0.6 makes it easier to iterate on feature engineering workflows by providing a number of capabilities that make it easier to develop, test, and deploy ML features.

Notebook-Driven Development with Tecton 0.6: Combating Fraud and Optimizing Dynamic Pricing

March 20, 2023

Notebook-driven development is a flexible and efficient approach that enables data scientists, ML engineers, and data engineers to define features in Python notebooks while constructing ML models.

Tecton 0.6 Enables Data Teams to Improve Iteration Speed When Building Batch, Streaming & Real-Time Features

March 15, 2023

The 0.6 release aims to provide a seamless transition from notebook development to production, the first feature platform to offer this capability

Choosing the Right Feature Store: Feast or Tecton?

December 22, 2022

See a side-by-side deep-dive comparison of Feast and Tecton.

Feature Store vs. Feature Platform

October 19, 2022

In part 2 of this 3-part series, we outline the differences between a feature store and a feature platform, and how they can help you overcome common challenges when building real-time ML in production.

Real-Time Machine Learning Challenges

October 19, 2022

In Part 1 of this series, we do a deep dive into the most common challenges of building real-time ML in production and why they're so challenging. Future posts will talk about how companies solve these challenges.

Getting Started With Amazon SageMaker & Tecton’s Feature Platform

February 23, 2022

SageMaker has emerged as a leading machine learning platform for enterprises running on AWS. Similarly, Tecton has emerged as the feature platform of choice for enterprises running machine learning (ML) in production. Tecton makes it very easy to …