Home Business Intelligence KNIME Analytics Platform

KNIME Analytics Platform

An open source analytics software
our rating 4.5 out of 5 Stars

KNIME Analytics PlatformProduct Overview

  1. About KNIME Analytics Platform
  2. Pros of KNIME Analytics Platform
  3. Cons of KNIME Analytics Platform
  4. Breakdown of core features

KNIME Analytics Platform product overview

KNIME Analytics Platform is a free, open-source software for designing and delivering data science workflows. It is intuitive, open, and continuously integrates new developments to help data science teams discover the potential hidden in data, mine for fresh insights, and predict new features. It can be downloaded locally but is also available on Azure and AWS cloud platforms. Today, KNIME users are applying the software across a wide range of industries including life sciences, financial services, retail, manufacturing, government, and research.

KNIME is written in Java and based on Eclipse, which comprises an integrated development environment and an extensible plug-in system. The software makes designing data science workflows and reusable components accessible to everyone. The KNIME company believes in open source and community. It maintains and develops an open source platform with all the functionality that an individual user might require. It delivers extended functionality through the work of the company and the community. Commercial extensions with yearly license fees are also available.

Pros of KNIME Analytics Platform

Back to top ↑

  • Visual workflows: KNIME Analytics Platform lets you create visual workflows with a drag-and-drop style graphical interface. Building and executing a workflow is easy without the need for any coding, although the platform allows it, too. Creating a workflow, for example, that will read, transform, and visualize sales data involves six short steps, from downloading the data to executing and opening the output visualization.
  • Nodes for all tasks: In KNIME Analytics Platform, nodes represent the tasks. These nodes with input and output ports can perform a variety of tasks for the entire data science workflow. Examples of dedicated tasks the nodes can perform are reading or writing files, transforming data, training models, or creating visualizations.

Cons of KNIME Analytics Platform

Back to top ↑

  • Support: KNIME is a European company, so teams located in distant regions or time zones face the challenge of immediate customer support when answers to issues are not found in documentation. User support from community forums can be very helpful.

Breakdown of core features

Back to top ↑

Multiple data sourcing

KNIME Analytics Platform lets users combine data from different sources. It can open and combine data from simple text formats such as CSV, XLS, XML, PDF, or JSON. The software can also work with unstructured data types such as images, documents, and networks, as well as time series data. It can connect to a host of databases and data warehouses to integrate data. Access and retrieve data from cloud apps, repositories, and services such as Salesforce, SharePoint, Azure, AWS, Google Sheets, or Twitter.

Data shaping

KNIME Analytics Platform allows powerful data manipulation with built-in tools and features. You can derive statistics or apply statistical tests to validate a hypothesis. Integrate dimensions reduction and correlation analysis into workflows. The software lets you aggregate, sort, filter, and join data residing on your local computer, inside a database, or in a distributed big data environment. Clean data through various processes and easily detect out of range values. You can also extract, select, or construct new features to prepare data sets for machine learning.

AI & machine learning

KNIME’s platform enables you to build machine learning models using visual nodes. Use the models for classification, regression, or clustering. Optimize model performance, validate models, or make predictions using validated models or with the use of predictive model markup language on Apache Spark.

Insight discovery & sharing

You can visualize data with classic and advanced types of charts, then customize them for your needs. Display summary statistics in a KNIME table and filter out what is irrelevant. Processed data and analytic results can be stored in many common file formats or databases. The software lets you export reports as PDF or Powerpoint for presentation purposes.

(Last updated on 02/02/2022 by Jose delos Santos)

Quick Facts

  • Industry Specialties
    All Industries
  • Pricing
  • Works Best For
    Any Sized Businesses




  • Multiple data source connections
  • Multiple data type compatibility
  • Data extraction, cleaning, combining, and manipulation
  • Formulas
  • Statistical tools
  • Drag-and-drop UI
  • Visual workflows
  • Nodular workflow designing
  • Machine learning models
  • Data visualization tools
  • Reports
  • Data/report exporting


  • KNIME Server
  • KNIME Hub
  • R
  • Python
  • Keras
  • H2O.ai
  • Apache Spark

Pricing Model

  • Free, open source
  • Commercial license


  • English