Accelerate the R&D process through reproducible data analytics, and effectively manage and use your data. KNIME is an open platform for the entire data science process: data access and transformation, visualization, predictive analytics, and reporting. KNIME Software allows anyone to create data science workflows (pipelines) and productionize them for use across the company.
Quick & Easy Prototyping
Data available at every step. Evaluate ideas and build prototypes without wasting time. Create visual workflows using an intuitive, drag and drop visual interface, without the need for coding. Access your data at every step so you can ensure everything is correct and evaluate the results during prototype building.
Collaborate with Domain Experts
Deploy Workflows with KNIME Server
Productionize data science applications and services
Deploy workflows across the enterprise as analytical services or applications. KNIME Server lets you share data and workflows, manage permissions, and track workflow revisions as well as automate and schedule workflow execution. Enterprises can respond efficiently to constantly changing demands by scaling workflow execution. Meet compute demands elastically and automatically with cloud offerings on AWS and Azure.
Future proof, no lock in, transparent pricing
KNIME Server has transparent pricing with no hidden costs for additional features. The underlying open source KNIME Analytics Platform sets no limitations on the amount of data, number of nodes, or ML techniques, and it's free to download.
- No limitations on using open source KNIME Analytics Platform, ever!
- Even if you discontinue the KNIME Server license, workflows can still be used in KNIME Analytics Platform without any limitations
Mix & Match Technologies
Due to the open nature of KNIME, you have extreme freedom in using any data source, technology, or tool - all in a single workflow.
Cheminformatics with KNIME & Extensions
With KNIME and its dedicated Cheminformatics Extensions you can choose from a wide range of cheminformatics functionality and create workflows. For example: finding chemical scaffolds using maximum common substructure, R-group decomposition, or multiobjective optimization.
Access Diverse Data
Access simple text formats, semantic data, or specific formats like SDF, RXN, SMILES, and MOL. Automatically retrieve data from public resources, or connect to AWS S3, Azure, and GCP. Connect to databases and data warehouses to integrate data from Oracle, Microsoft SQL, Hadoop, Google BigQuery, and more.
Data Science Technologies
Build machine learning models for classification, regression, dimensionality reduction, or clustering. Integrate with Tensorflow, Keras, H2O, and others. Use your favourite packages in R or Python and combine with other KNIME functionality in one reproducible workflow.
- Blog: How to use Python code in Jupyter notebooks within KNIME, and how to execute KNIME workflows from within Python
- Blog: How to work with the Semantic Web Technologies
- Blog: Learn how to access data from diverse SQL type databases and merge it