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

March 31, 2023 by

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. Tecton’s Feature Platform ultimately saves development time and makes it …

Feature PlatformsFeature StoresProduct Updates

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

March 20, 2023 by

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.

Feature PlatformsFeature StoresFraud Detection

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

March 15, 2023 by

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

Feature PlatformsFeature Stores

Choosing the Right Feature Store: Feast or Tecton?

December 22, 2022 by ,

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

Feature PlatformsFeature Stores

Feature Store vs. Feature Platform: Which One Is Right for Your Team?

October 19, 2022 by ,

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.

Feature StoresFeature Platforms

Real-Time Machine Learning Challenges

October 19, 2022 by ,

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.

Feature PlatformsFeature Stores

Why Feature Stores Should Extend, Not Replace, Existing Data Infrastructure

May 11, 2022 by

During apply(meetup), Ben Wilson, from Databricks, gave a lightning talk on how ML projects shouldn't be built in isolation. At Tecton, we believe that great ML infra should integrate deeply with existing data infrastructure while providing …

Thought LeadershipFeature Stores

Building a Feature Store

January 20, 2022 by

As more and more teams seek to institutionalize machine learning, we’ve seen a huge rise in ML Platform Teams who are responsible for building or buying the tools needed to enable practitioners to efficiently build production ML systems. Almost …

Feature StoresThought Leadership

Announcing Feast 0.10

April 15, 2021 by

Today, we’re announcing Feast 0.10, an important milestone towards our vision for a lightweight feature store.  Feast is an open source feature store that helps you serve features in production. It prevents feature leakage by building training …

Feature StoresAnnouncements

How to Build a Fraud Model With a Feature Store

April 5, 2021 by

Many companies with platforms that involve financial transactions are looking to bring them in-house to some degree as they can have more control over the user experience and usually save money on transaction fees over outsourced solutions. While the …

TutorialsFeature Stores

Amazon SageMaker & Tecton: How to Choose the Right Feature Store on AWS

December 10, 2020 by

Amazon recently introduced the SageMaker feature store, recognizing that one of the largest challenges facing data science teams is building and serving high-quality machine learning features both in training and in production. We at Tecton …

Feature Stores

Feature Store in General Availability & Series B Funding

December 6, 2020 by

Today marks a big milestone for Tecton. We’re excited to announce that the Tecton feature store is now in General Availability, and that we have raised $35 Million in Series B funding from our existing lead investors, Andreessen Horowitz and …

AnnouncementsFeature Stores