Benefits and Insights

Why use KNIME?

Key differentiators & advantages of KNIME

  • Open-Source: Users can join a network of thousands of users, enabling collaboration and support. The source code is free to download and can be accessed for editing.  
  • Free To Use: Businesses save money by getting access to all of the platform’s features for free. Licensed productivity and collaboration extensions are available at a cost. 
  • Increased Business Intelligence: Users get digestible, actionable data to make informed business decisions. Aggregation of large datasets into predictive and prescriptive models via easy-to-consume visualizations and summary statistics gives users projections for best course of action.  
  • Scalable: Businesses obtain access to big data by scaling up the project in-platform. Integrations to distributed and multi-threaded data processing allows projects to grow. 
  • End-To-End Analytics:  Businesses do not need to implement additional software to complete a data project. The platform is capable of handling some tasks from start to finish without integrations. Additional integrations may be required for increasing scale and completing more sophisticated analytics. 

Industry Expertise

The KNIME platform originated in 2004 at the University of Konstanz in Germany. It has more than 15,000 regular users in at least 60 countries, spanning industries such as pharmaceutical, CRM, financial analysis and life sciences.

Key Features

  • Sharing and Collaboration: KNIME Hub is an online repository for existing workflows, nodes and extensions that can be easily installed into a user’s workflow. Users can upload their own workflows and search for the components they need for their projects. 
  • In-database or Distributed Processing: It can process data in-database or on a distributed cluster like Apache Spark for increasing scale. It has prebuilt workflows for in-database processing, like in SQL Server. 
  • Model Predictions and Validation: Using machine learning and AI, it can produce predictive and prescriptive models. It can use performance metrics such as AUC and R2 to verify models.  
  • Visual Workflows: A drag-and-drop interface lets users compose a workflow with little to no coding. Prebuilt generic workflows and components can be downloaded from KNIME Hub. 
  • Data Management: The platform handles all steps of the extract, transform and load process. It can ingest, blend, prepare, cleanse and store structured and unstructured data. It can combine data types, including PDF, JSON, CSV and unstructured types like documents and images. 
  • Data Visualizations: Analysis can be compiled into reports with heat graphs, bar charts, scatter plots, and more. Visualizations can be exported as PDFs, PowerPoints or other formats.  
  • Tool Blending: Tools with unique domains can be combined within a workflow via native nodes. These include Python or R scripting, processing connectors, machine learning and AI. 


Some of the product limitations include:
  •  It does not offer monthly billing, only annual 
  •  It requires five users and eight cores to qualify for an annual subscription 
  •  Lacks integration with Jupyter Notebooks 
  •  Doesn’t offer phone support 

KNIME Suite Support

Because of the open-source nature of KNIME, it relies heavily on a community forum for support. The forum has nearly 10,000 users, including KNIME personnel to assist users. Traditional support is described below.
mail_outlineEmail:Email support is fulfilled by the ticketing system, described below.
phonePhone: Phone support is not provided.
schoolTraining: The vendor offers a “Learning” section on its website, offering FAQs, documentation, white papers, webinars and training courses. Courses take place over a period of time, and vary from free or for a price. Certification is available.
local_offerTickets: Users can submit a support ticket through the “Contact” page on the vendor’s website.
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