Hopsworks 1.x series brings many new features and improvements, ranging from services such as the Feature Store and Experiments, to enhanced support for distributed stream processing and analytics with Apache Flink and Apache Beam, to building Deep Learning pipelines with TensorFlow Extended (TFX), to code versioning support for Jupyter notebooks with Git, to all-new provenance/lineage of data across all steps of a data engineering and data science. We are also excited that Hopsworks 1.x is the back-bone of the all new Managed Hopsworks platform for AWS, Hopsworks.ai (https://www.hopsworks.ai/).
On September 5th, 2019, Logical Clocks won the European DatSci award for “Data Science Technology Innovation of the Year”. Hopsworks is a data-intensive platform for data science and AI, that includes the first Enterprise Feature Store for Machine Learning.
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.
Announcing the release of the first Enterprise Feature Store for Machine Learning. The Feature Store solves the problem of ad-hoc and siloed machine learning pipelines, where features, the training data for such pipelines, tend to become disorganized, disjointed, and duplicated, leading to correctness problems and redundant work.
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.