Add On-demand transformations support
Add Data quality monitoring
Add Snowflake offline store support
Add Bigtable support
Add Push/Ingestion API support
Ensure Feast Serving is compatible with the new Feast
Decouple Feast Serving from Feast Core
Add FeatureView support to Feast Serving
Update Helm Charts (remove Core, Postgres, Job Service, Spark)
Add Redis support for Feast
Add direct deployment support to AWS and GCP
Add Dynamo support
Add Redshift support
Full local mode support (Sqlite and Parquet)
Provider model for added extensibility
Firestore support
Native (No-Spark) BigQuery support
Added support for object store based registry
Add support for FeatureViews
Added support for infrastructure configuration through apply
Remove dependency on Feast Core
Feast Serving made optional
Moved Python API documentation to Read The Docs
Moved Feast Java components to feast-java
Moved Feast Spark components to feast-spark
Added Feast Job Service for management of ingestion and retrieval jobs
Added support for Spark on K8s Operator as Spark job launcher
Added Azure deployment and storage support (#1241)
Note: Please see discussion thread above for functionality that did not make this release.
Add support for AWS (data sources and deployment)
Add support for local deployment
Add support for Spark based ingestion
Add support for Spark based historical retrieval
Move job management functionality to SDK
Remove Apache Beam based ingestion
Allow direct ingestion from batch sources that does not pass through stream
Remove Feast Historical Serving abstraction to allow direct access from Feast SDK to data sources for retrieval
Label based Ingestion Job selector for Job Controller #903
Authentication Support for Java & Go SDKs #971
Automatically Restart Ingestion Jobs on Upgrade #949
Structured Audit Logging #891
Request Response Logging support via Fluentd #961
Feast Core Rest Endpoints #878
Batch statistics and validation #612
Authentication and authorization #554
Online feature and entity status metadata #658
Improved searching and filtering of features and entities
Python support for labels #663
Improved job life cycle management #761
Compute and write metrics for rows prior to store writes #763
Streaming statistics and validation (M1 from Feature Validation RFC)
Add feature and feature set labels, i.e. key/value registry metadata (#463)
Job management API (#302)