KNIME Software
Predictive analytics software
Statistical analysis software
Data science and machine learning platforms
Dashboard software
KPI software
Low-code machine learning platforms software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
Take the quiz to check if KNIME Software and its alternatives fit your requirements.
$19 per month
Free TrialFree version
Small
Medium
Large
- Professional services (engineering, legal, consulting, etc.)
- Retail and wholesale
- Agriculture, fishing, and forestry
What is KNIME Software
KNIME Software is a data analytics, data science, and machine learning platform centered on a visual, node-based workflow builder. It is used by data analysts and data scientists to prepare data, build and evaluate models, and operationalize analytics through reusable workflows and integrations. The platform includes a free desktop application and commercial server capabilities for collaboration, governance, and deployment. It differentiates through its low-code workflow approach, broad connector ecosystem, and support for extending workflows with code (for example, Python and R).
Visual, low-code workflows
KNIME’s node-based interface supports building end-to-end analytics pipelines without requiring extensive coding. Workflows make data preparation, feature engineering, and model evaluation explicit and repeatable. This approach can reduce handoff friction between analysts and data scientists compared with code-only notebooks. It also supports mixing low-code nodes with scripted steps when needed.
Broad integration and extensibility
KNIME provides connectors and nodes for common data sources, file formats, and analytics tasks, and it supports extensions from its community and partners. It integrates with Python and R so teams can reuse existing libraries and custom code within governed workflows. This helps organizations standardize pipelines while still accommodating specialized methods. The extension model also enables adding domain-specific functionality over time.
Collaboration and deployment options
With server components, KNIME supports sharing workflows, managing versions, and controlling access for teams. It can schedule and automate workflow execution to support recurring analytics and data processing jobs. Deployment patterns include publishing workflows and exposing results to downstream systems, which helps move from experimentation to operational use. These capabilities provide an alternative to BI-first tools when the primary need is pipeline automation and model execution.
Dashboarding is not primary
KNIME includes reporting and visualization capabilities, but interactive dashboarding and KPI monitoring are not its primary focus. Organizations that need highly polished executive dashboards may still require a dedicated BI layer. As a result, KNIME often serves upstream for data prep and modeling rather than as the final analytics consumption interface. This can add an extra tool in the stack for reporting-heavy use cases.
Learning curve for complex flows
While basic workflows are approachable, complex pipelines can become large and harder to navigate without strong conventions. Teams typically need governance practices (naming, modularization, documentation) to keep workflows maintainable. Debugging multi-branch workflows can be less straightforward than stepping through code in some environments. New users may also need time to understand node configuration and execution behavior.
Enterprise features require licensing
The free desktop application covers many individual-use scenarios, but collaboration, centralized governance, and production deployment commonly depend on commercial server offerings. This can increase total cost for organizations that need multi-user management, scheduling at scale, and controlled promotion across environments. Some advanced integrations and administrative controls may also be tied to paid editions. Buyers should validate which capabilities are included in each tier for their deployment model.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| KNIME Analytics Platform (desktop) | Free | Open-source desktop application; build/run workflows locally; 300+ connectors; unlimited local execution; optional Personal account gives K‑AI assistant (20 interactions/month), access to self-paced courses and KNIME forum. |
| KNIME Hub — Personal (online) | Free | Personal cloud space on KNIME Hub; public spaces; 2 versions/workflow; 20 K‑AI interactions/month (Personal account). |
| Pro | Starts at $19 / month (or €19 / month) | For individuals who need automation: includes 120 execution credits for workflow runtime, ability to deploy/share workflows as Data Apps (120 credits included), 500 K‑AI interactions/month included; additional runtime charged at $0.025 per vCore‑minute; additional K‑AI interactions charged $0.025 per 5 requests; option to extend disk space (30 GB included); unlimited versioning. (See KNIME pricing page.) |
| Team | Starts at $99 / month (or €99 / month) | For small teams: all Pro features plus collaboration in private spaces (3 team members included; additional members at $49/month each), centralized billing; includes 120 execution credits; try-for-free available. |
| Business Hub | Pricing available on request | Enterprise offering: schedule/run workflows, team collaboration with fine-grained permissions, enterprise governance (LDAP/OAuth/OIDC, SCIM), dedicated execution resources, customization and enterprise support; contact KNIME/sales for pricing. |
Seller details
KNIME AG
Zurich, Switzerland
2008
Private
https://www.knime.com/
https://x.com/KNIME
https://www.linkedin.com/company/knime/
