Knime
Analyze Data, Upskill, Scale, No Coding Required. [Contact for Pricing]
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What is Knime?
KNIME is an open-source data science platform that enables users to access, blend, clean, analyze, and visualize data without requiring coding skills. The KNIME Analytics Platform uses a intuitive drag-and-drop visual workflow interface where users connect icons representing data processing steps, making it easy to learn while supporting complex analyses from data preparation to machine learning and AI/LLM integration.
Key features include 300+ connectors to data sources (desktop applications, databases, data warehouses), support for all file formats, interactive data visualizations with dozens of chart types, automated workflow generation with a genAI assistant (K-AI), integration with popular machine learning libraries, and the ability to embed Python, R, and JavaScript scripting. Users can bundle workflow segments as reusable components, deploy workflows as data apps or REST APIs, and collaborate on visual workflows with version control.
KNIME is designed for data analysts, data scientists, business analysts, researchers, and anyone working with data who wants to avoid coding. It serves individuals, small teams, and large enterprises across all industries. The platform has a community of over 300,000 users in 60+ countries and over 100,000 Analytics Platform users who access the KNIME Community Hub with 14,000+ community-built data science solutions.
Knime pricing
Pricing model: Freemium
KNIME offers a free and open source KNIME Analytics Platform for personal use with unlimited local workflow building and execution. KNIME Hub (Online) has three paid plans: Personal plan starts at $19/€19/month with 500 K-AI interactions/month + pay-as-you-go, Pro plan starts at $99/€99/month for individuals needing automation and deployment, and Team plan starts at $39,900/€35,000/year for larger teams. The Personal plan includes 2 versions per workflow and starts at $0.025/minute for execution. KNIME Business Hub has Basic (5 users, 4 vCores included), Standard (5 users, 8 vCores), and Enterprise (20 users, 16 vCores) plans with pricing available on request. All paid plans include 120 execution credits with additional execution at $0.025/minute. Free trials are available for Pro and Team plans.
Knime pros
- Free and open source with no cost for the Analytics Platform
- No coding required - drag-and-drop visual workflow interface
- 300+ connectors to data sources including databases and cloud services
- Integrates with all popular machine learning libraries including LLMs
- genAI assistant (K-AI) for automatic workflow generation and guidance
- Interactive charts and visualizations for data exploration
- Automates repetitive and manual data manipulation tasks
- Supports Python, R, and JavaScript scripting integration
- Reusable components allow bundling workflow segments
- Deploy workflows as data apps or REST APIs for sharing insights
- Version control for collaborative workflow development
- Large community with 300,000+ users and 14,000+ solutions
- Self-paced and guided courses available for upskilling
- Works on Windows, Mac, and Linux operating systems
- Blends data of any size and any type from any source
- In-database and distributed big data environment support
- Enterprise support available for Business Hub customers
Knime cons
- Learning curve for complex workflows despite no-code interface
- Some algorithms may require too much time and memory for huge datasets
- Free tier limited to 20 K-AI interactions per month
- Node Description window doesn't work on some Linux distributions
- Batch execution no longer supported as of 2026
- Anti-virus software may prevent Java VM from allocating memory on Windows
- Legacy Swing dialogs don't work on Linux with Wayland
- HTTP connections with authentication behind proxy require knime.ini workaround in version 5.1+
- Out of memory errors possible with large database reads without fetch size adjustment
- Startup can be slow due to antivirus scanning plugins
Frequently asked questions about Knime
What is KNIME and what does it stand for?
KNIME stands for Konstanz Information Miner and is pronounced [naim] (with a silent 'k', like in 'knife'). It is developed by KNIME AG in Zurich and was created by the group of Michael Berthold at the University of Konstanz, Chair for Bioinformatics and Information Mining. KNIME is an open source platform built to productionize data science from day 1.
How much data can I process with KNIME?
Basically, there are no limits since the data is buffered in an intelligent way. However, some algorithms may require too much time and memory for very huge datasets. KNIME can access and blend data of any size and any type, with all file formats supported.
Can I use KNIME for commercial purposes?
Yes. KNIME is available under a dual licensing model. The open source version is free and can be used for commercial research, instruction, noncommercial research, or administrative purposes. Students, faculty, and staff may use it for any purpose since it's open-source software. If you need different license terms than the open source license, you can contact KNIME.
How do I increase Java Heap Space for KNIME?
In the KNIME installation directory, open the knime.ini file. Find the entry -Xmx1024m and change it to -Xmx4g or higher. Then restart KNIME. On Mac, right-click KNIME.app, select 'Show package contents', go to '/Contents/Eclipse/' to find knime.ini. On Linux it might be .knime.ini.
What kind of data is transmitted when I send anonymous usage data?
KNIME transmits: version of KNIME Analytics Platform used, anonymized installation ID, how long KNIME runs, how many times it was launched and exited successfully, how many workflows were opened, how often workflows were imported/exported, and which nodes were used with execution statistics. KNIME does NOT transmit any settings or configuration of nodes, any data used in workflows, or any other personal data.
What is the difference between KNIME Analytics Platform, KNIME Community Hub, and KNIME Business Hub?
KNIME Analytics Platform is for building analytic solutions locally on your desktop (free and open source). KNIME Community Hub is for individuals and small teams to build and share workflows privately or publicly with the open source community. KNIME Business Hub is for larger teams with business needs to build, share, deploy, and scale in a private environment with governance, collaboration, and enterprise features.
Which version of Java does KNIME Analytics Platform rely on?
A Java Runtime Environment (JRE) is packaged with each KNIME Analytics Platform installation, so no separate Java installation is needed. Starting with version 4.4, KNIME comes with Java 11 runtime built and maintained by AdoptOpenJDK. Previously, version 3.7 and older shipped with Oracle Java 8 JRE.
How do I create a new project in KNIME?
In the Navigator view (left top window), right-click and select 'New', then 'New KNIME Project'. Provide a name for the new project and click the OK button.
What if the Node Repository shows only a few nodes or none at all?
Check if you have something entered in the search field of the Node Repository view. Click into the edit field at the top of that view and delete any search term that might be present, including blank characters or spaces. This should return all nodes included in the installation. If this doesn't help, your installation might be damaged.
How can I force KNIME to cache intermediate data to disk to reduce memory usage?
In a node's dialog, go to the tab 'General Node Settings' where three memory policies are available: 'Keep all in memory', 'Write tables to disc', and 'Keep only small tables in memory' (the default). To change the threshold, add this line after -vmargs in knime.ini: -Dorg.knime.container.cellsinmemory=1000 (or your preferred value). This controls how many cells to keep in memory before swapping to disk.