Integrate Big Data, Machine Learning, AI, Scripting, and more.
Conduct predictive analytics and scoring on Apache Spark using PMML models and integrate complex statistics and machine learning with SparkML or H2O Sparkling Water. Visual programming allows code-free, big data science, while scripting of jobs allows detailed control when needed.
Import, export, and access data with Hive, Impala, H2, HDFS, or KNIME Analytics Platform.
Mix and match local and Hadoop workflow executions within the same workflow.
Add PySpark jobs to your existing Spark workflow. Our Python editor allows code validation directly within the cluster for rapid prototyping.Learn more
R and Python Scripting
Add custom functionality with native R, Python (versions 2 and 3), and Java scripting capabilities - from custom Apache Spark jobs, to visualisations or advanced analytics, and machine learning.
Run scripts seamlessly in combination with other KNIMEnodes within a single workflow. Document individual steps, allowing for large scale deployment.
Import and run code from Jupyter notebooks - your code can stay in Jupyter but still be used from within your KNIME workflows.
H2O Machine Learning
Take advantage of H2O machine learning and choose from a variety of high performance algorithms including Gradient Boosted Trees, Generalized Linear Models, Random Forest, and Isolation Forests.
Train and validate models in H2O using data partitioners, cross validation, binomial, and multinomial scoring.
Scale execution with H2O Sparkling Water. Seamlessly combine H2O nodes with KNIME Extension for Apache Spark.
Integrate with existing KNIME nodes for data prep and cleansing, visualisation, or hyper parameter optimisation, combining them directly with H2O functionality.KNIME Analytics Platform and H2O
Load, create, edit, train, and execute deep neural networks within KNIME Analytics Platform.
Access a variety of cutting edge deep learning frameworks, such as Keras, Tensorflow, or ONNX.
Create and train deep network architectures without writing a single line of code using the KNIME Keras Integration.
Fine tune trained networks to your analysis problem. A rich variety of unstructured (text, images, etc) and structured data types can directly be used for training and prediction.
Google Drive Connectivity
Read from and write to both "My Drive" and "Team Drive" and use files you've stored in Google Drive. Access data from a Google Sheet, write information to new sheets, or modify existing sheets.
Carry out various tasks such as reading or adding headers, substituting missing values, and automatically opening Google Sheets.
Log in directly from the node configuration or provide credential files (if preferred).
Search for Tweets on Twitter, retrieve information about users, Tweet directly via KNIME, and more.
Visualize geo-spatial information with open street maps.
Integrate XGBoost's Linear Ensemble or Tree Ensemble learners for either classification or regression in your KNIME workflows.
Get started with KNIME
Download KNIME Analytics Platform and build your first workflow.
Install integrations for KNIME
Learn how to install extensions for KNIME Analytics Platform.
Join the community
Join our KNIME community, share ideas, and find answers to your data science challenges.