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Hopsworks 3.8 is now generally available. This new release adds a notification service to the Hopsworks platform allowing changes to Feature Groups to result in notifications being sent to relevant subscribers. In addition a number of improvements have been made to transformation functions including model dependent transformations and on-demand transformations. In addition a number of minor improvements were included with this release.
Hopsworks 3.7 is now generally available. This new release adds additional capabilities to support LLM/GenAI use cases, introduces feature monitoring, integrates support for Delta Lake and provides a new notification service to track changes to specific features.
Hopsworks 3.5 is now generally available. This version brings enhancements to the feature view APIs, improved management of Airflow Dags when utilizing Airflow embedded in Hopsworks, compatibility with newer Databricks runtimes, and various updates to dependencies.
Hopsworks 3.4 is now generally available. This version adds support for multi-region high availability and integration with external Kafka clusters. With 3.4, we now allow users to customize the operating system libraries in their Python environment. We have also added new support for scheduling Python and Spark jobs (e.g., used to orchestrate machine learning pipelines).
Hopsworks 3.3 is now generally available. This version includes two new APIs to retrieve data for batch inference (built using DuckDB and ArrowFlight server) and a REST API to retrieve data from the online feature store.
Read about Hopsworks 3.1 and the new improvements in the feature store (time-series splits for training data, support for managing thousands of models), stability and user-interface.
Hopsworks 3.0 is a new release focused on best-in-class Python support, Feature Views unifying Offline and Online read APIs to the Feature Store, Great Expectations support, KServe and a Model serving
We go through the new features and developments in Hopsworks 2.5 that will benefit open-source users and customers alike.
Logical Clocks, the data company behind the world’s first Enterprise Feature Store for Machine Learning, today announced full support for Microsoft Azure on its cloud managed data platform, Hopsworks. The announcement complements the existing support for Amazon Web Service (AWS), thus enterprises can now manage features for training and serving models at scale on Hopsworks while maintaining control of their data inside their organisation’s accounts on the most popular cloud platforms.
Hopsworks 0.10 brings the latest features, improvements and bug fixes. It is the biggest release done so far, made up of 191 JIRAs including many new features. Also, this version marks the last of the 0.x series, as Hopsworks is gearing up towards its 1.x series starting with 1.0 end of Q3 2019.
Hopsworks 0.9.0 brings the latest features, improvements and bug fixes. It introduces Apache Airflow as-a-service which means users can now create their own workflows from within their familiar environment of a Hopsworks project. You can get started with Airflow in Hopsworks by visiting the user-guide.
Hopsworks 0.8.0 brings the latest features, improvements and bug fixes. It comes a short while after version 0.7.0 and brings the world’s first open-source feature store, a revamped REST API for managing jobs in Hopsworks and improvements in visualization for python notebooks.
