Feast

Feast

Tecton
+
+

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About

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. For example, in an application that recommends a music playlist, features could include song ratings, listening duration, and listener demographics. Features are used repeatedly by multiple teams and feature quality is critical to ensure a highly accurate model. Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. SageMaker Feature Store provides a secured and unified store for feature use across the ML lifecycle. Store, share, and manage ML model features for training and inference to promote feature reuse across ML applications. Ingest features from any data source including streaming and batch such as application logs, service logs, clickstreams, sensors, etc.

About

Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Enterprises seeking a solution to store, share, and manage ML model features for training

Audience

Anyone looking for an open-source feature store which provides easy access to consistent features across model training and online inference

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Amazon
Founded: 1994
United States
aws.amazon.com/sagemaker/feature-store/

Company Information

Tecton
Founded: 2019
United States
feast.dev/

Alternatives

Alternatives

JFrog ML

JFrog ML

JFrog

Categories

Categories

Integrations

Amazon Redshift
Amazon S3
Databricks
Snowflake
AWS Glue
AWS Lake Formation
Amazon DynamoDB
Amazon ElastiCache
Amazon SageMaker Data Wrangler
Amazon Web Services (AWS)
Apache Kafka
Apache Spark
DataHub
Flyte
PySpark
Ray
Redis
TensorFlow
ZenML

Integrations

Amazon Redshift
Amazon S3
Databricks
Snowflake
AWS Glue
AWS Lake Formation
Amazon DynamoDB
Amazon ElastiCache
Amazon SageMaker Data Wrangler
Amazon Web Services (AWS)
Apache Kafka
Apache Spark
DataHub
Flyte
PySpark
Ray
Redis
TensorFlow
ZenML
Claim Amazon SageMaker Feature Store and update features and information
Claim Amazon SageMaker Feature Store and update features and information
Claim Feast and update features and information
Claim Feast and update features and information