Take a Virtual Tour of the Latest KNIME Software Release
Watch videos of all the major updates below.
Combine the best of visual programming and scripting with two major updates to the Python Integration. Developers writing custom KNIME nodes can choose to do so completely in Python and easily share these solutions with the team like any other KNIME extension. Better yet, Python environment is built-in. No need to install extra software.
Users can now build Machine Learning models in H2O.ai using Snowflake data in KNIME and push them to Snowflake for execution–so data doesn’t have to leave Snowflake. Users with or without coding experience can get insights on Snowflake data using KNIME’s intuitive low-code/no-code interface.
See a preview of a new-and-improved UX. KNIME newbies can get started building workflows much more quickly with the new and improved user interface. Experienced KNIME users can focus more deeply on data science. Much of the new design is based on feedback from you, the community.
Database enhancements and Azure services extend connectivity. Advanced ETL operations can be handled elegantly thanks to the new improvements to the Column Expression node, which now allows access to previous/subsequent rows, crucial for “between rows” calculations. And updates to the XGBoost extension improve the insights you get on features strongly affecting prediction outcomes.
Find details on these capabilities and more on our What’s New page.
What’s New in KNIME Analytics Platform 4.6.0 and KNIME Server 4.15
Read a summary of all the updates included in the latest release.
Test New Features with Example Workflows
Start using the newest features right-away with pre-built example workflows, now available on KNIME Hub.