KNIME
UnclaimedOpen-source data analytics and machine learning platform for visual workflow creation.
Visit WebsiteReviews onG2Capterra
330 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Free and open-source desktop version for personal use
Biggest con
Advanced collaboration and enterprise features require paid subscriptions
TL;DR - KNIME
- Build visual workflows for data processing, analysis, and machine learning.
- Connects to over 300 data sources and handles diverse data types.
- Offers free desktop platform with paid options for collaboration, automation, and enterprise governance.
Pricing: Free plan available
Best for: Growing teams
4.5/5 across review platforms
What is KNIME?
KNIME Analytics Platform is an open-source data science platform that enables users to build and execute visual workflows for data processing, analysis, and machine learning. It supports connecting to over 300 data sources and services, processing various data types including numerical, categorical, text, images, time-series, and even molecule or network data. Users can perform analytics ranging from simple statistics to advanced machine learning and Generative AI, and integrate visual workflows with code.
KNIME is designed for a wide range of users, from individual data scientists and citizen data scientists to large enterprises. It helps organizations reduce supply chain disruptions, improve production quality, and boost profitability by providing better insights into manufacturing processes. The platform is known for its ease of learning and adoption, making it suitable for training programs aimed at upskilling employees in data analytics.
Available on: Web, Windows, macOS, Linux
Pros & Cons
Pros
- Free and open-source desktop version for personal use
- Easy to learn and adopt, suitable for citizen data scientist training
- Highly flexible and intuitive for prototyping and adapting to new data structures
- Supports a wide range of data types and analytical complexities
- Integrates with existing tools like Excel, JMP, Minitab, Tableau, Matlab, Python, and R
Cons
- Advanced collaboration and enterprise features require paid subscriptions
- Workflow runtime beyond included credits incurs additional costs
- Full comparison of pricing features is best viewed on a larger screen, indicating potential complexity
Ratings Across the Web
4.5(330 reviews)
Ratings aggregated from independent review platforms. Learn more
Preview
Key Features
Visual workflow builder with drag-and-drop nodesConnect to 300+ data sources and servicesProcess numerical, categorical, text, image, time-series, molecule, and network dataPerform statistical analysis, machine learning, and GenAIInterleave visual workflows with code (Python, R)Automate workflows on schedulesDeploy workflows as data apps and REST servicesCollaborate in private spaces with fine-grained permissions
Pricing Plans
Free TrialKNIME Analytics Platform
Free
- Connect to 300+ data sources and services
- Process & analyze data of any size or type
- Perform analytics of any complexity
- Write to files, databases or services and generate reports
- Interleave visual workflows with code
- Optionally, get access to our K-AI assistant (20 interactions / month), self-paced courses, and the KNIME forum with a free Personal account
Pro
$19 / month
- Run and automate workflows (120 credits for workflow runtime included)
- Deploy and share workflows as data apps (120 credits for workflow runtime included)
- Additional workflow runtime beyond included credits: $0.025 per vCore minute
- Store and use secrets securely
- Optionally, extend disk space (30 GB included)
- Build workflows assisted by K-AI (500 interactions / month included, $0.025 for every 5 requests after)
- Unlimited versioning
Team
$99 / month
- All from Pro, plus
- Collaborate in private spaces (3 team members included, additional at $49/month)
- Centralized billing on team level
Business Hub
Pricing available on request
- Automate running and deploy workflows — schedules, data apps and services
- Collaborate in and across teams with fine granular permissions
- Manage at enterprise level — LDAP, OAuth/OIDC etc.
- Govern the way you need — staged deployment, GenAI gateway
- Scale execution and dissemination securely — dedicated resources, secrets, SCIM etc.
- Customize extensions and code environments
- Get enterprise support in US and EU business hours or more
How KNIME's pricing compares
At $19/mo, KNIME is mid-range of its 5 direct competitors ($10 to $250/mo across the set).
Entry paid plan, monthly.
Reviews
4.5/5
Across 330 verified user reviews on G2, Capterra
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KNIME FAQ
How does KNIME Analytics Platform handle multi-threading for data queries, especially when dealing with large datasets from various locations?
KNIME Analytics Platform allows for multi-thread parallel queries by simply dragging and dropping nodes within a workflow. This visual approach eliminates the need for sophisticated coding skills, significantly reducing the time required to develop solutions for complex data retrieval, such as pulling data from geographically dispersed sources like Asia, as demonstrated by Seagate's use case.
Can KNIME integrate with existing data science tools and infrastructure commonly used in manufacturing or R&D environments?
Yes, KNIME is designed to slot in with existing tools and infrastructure. It can integrate with popular data science tools such as Excel, JMP, Minitab, Tableau, Matlab, Python, and R, allowing organizations to leverage their current investments while adopting KNIME for advanced analytics.
What is the role of the K-AI assistant in KNIME, and how does its usage differ across the various pricing tiers?
The K-AI assistant helps users build workflows. In the free Personal account, users get 20 interactions per month. The Pro plan includes 500 interactions per month with a pay-as-you-go option for additional requests, while the Team plan offers 500 interactions per user per month, also with a pay-as-you-go option. The Business Hub also leverages the K-AI assistant, with specific details available upon request.
Beyond basic data processing, what specific types of advanced analytics can be performed with KNIME, particularly in a manufacturing context?
In a manufacturing context, KNIME can be used for advanced analytics such as dynamic modeling of downstream metrics in complex processes like recording head manufacturing. This enables early detection of processing issues, significantly reducing the risk of material loss and improving overall production quality and efficiency, as evidenced by Seagate's ability to save over $1M by identifying issues earlier.
How does KNIME support the concept of 'Citizen Data Scientists' within an organization, and what resources are available for their training?
KNIME is integral to 'Citizen Data Scientist' training programs due to its ease of learning and visual workflow approach. Organizations like Seagate have implemented tailored training programs, including online and onsite trainings and workshops, to upskill employees from beginners to analytics practitioners. The platform's intuitive interface, likened to 'building with Lego,' allows individuals to quickly prototype ideas and adapt workflows without extensive coding knowledge.
What are the deployment options for workflows built in KNIME, and how do they scale for enterprise needs?
Workflows built in KNIME can be deployed as data apps to other users or as REST services. For enterprise needs, the KNIME Business Hub offers advanced capabilities to automate running and deploy workflows via schedules, data apps, and services. It provides enterprise-level management features such as LDAP, OAuth/OIDC authentication, fine-grained permissions, staged deployment for quality control, and secure scaling with dedicated resources and SCIM integration.
Source: knime.com