KNIME Analytics Platform

KNIME Analytics Platform

KNIME Analytics Platform is an open-source software for creating visual workflows to access, transform, analyze, model, and visualize data. It connects to over 300 data sources and services, processes data of any type or size, and supports everything from simple analytics to complex machine learning and generative AI tasks. Users build workflows by connecting nodes that perform discrete actions on data. The platform allows interleaving visual workflows with code (Python, R, etc.) and includes a built-in AI assistant (K-AI). It is designed for business & domain experts, data experts, and end users to derive insights without heavy coding, as well as for MLOps and IT teams to deploy and monitor solutions.

Analytics
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Added on
Sep 18, 2026
Visual workflows300+ connectorsGenAI assistantOpen sourcePython integrationEnterprise deployment
Product information

Everything worth knowing about KNIME Analytics Platform

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Visual Workflow Builder
Build and edit data workflows using an intuitive, node-based visual interface. No coding required for core tasks.
Broad Data Connectivity
Connect to over 300 data sources and services, including databases, cloud storage, and APIs.
K-AI Assistant
Get AI-powered assistance for building workflows and scripting. Free tier includes 20 interactions/month.
Workflow Automation & Deployment
Automate workflows on schedules, deploy them as Data Apps or REST services for other users.
Technical capabilities
Hybrid Code Integration
Interleave visual workflows with code. Supports Python scripting with managed environments and extensions.
Enterprise Governance & Scaling
Features include LDAP/OAuth authentication, SCIM sync, staged deployment, and dedicated execution resources.
Must watch videos
How Citi Eliminated Shadow IT with Knime
6:33
Tutorial6:33
How Citi Eliminated Shadow IT with Knime
How do you replace shadow IT with analytics that can actually scale across a global enterprise? 👨‍💻 In this Citi success story, James Whelan, FMCR Technology Site Lead Head of Product & Functions Technology at Citigroup, shares how Citi deployed Knime to automate critical processes, bring business-built solutions under enterprise governance, and scale analytics across the organization. Today, Citi has 1,000+ unique Knime workflows in production, executes up to 750 data tasks per hour, and has reduced vulnerabilities by 80%. 🎥 🔴 ▶ Discover the full Citi success story and learn how KNIME helps enterprises scale analytics securely: https://www.knime.com/success-story/how-citi-eliminated-shadow-it?utm_medium=organic-social&utm_source=youtube&utm_campaign=financial_analytics&utm_term=video&utm_content=video #financeanalysis #knime #enterpriseai #businessanalytics
Governed Virality: How to Scale Analytical Insight Fast
4:06
Tutorial4:06
Governed Virality: How to Scale Analytical Insight Fast
Enterprise AI isn’t just about making better decisions — it’s about getting people to agree on them. But when everyone is working with their own data, analyses, and AI-generated answers, how do you turn individual insights into trusted decisions across an organization? 👨‍💻 In this excerpt from his talk “Lightning in a Bottle” at the KNIME Data Summit New York, Trevor Kaufman, CEO of KNIME, explores why the LLM experience is fundamentally a “single-player game” and why vibe-coded, self-service analytics don’t scale across the enterprise. He introduces the idea of governed virality — enabling trusted insights to spread quickly across an organization without losing governance, context, or trust. 🎥 🔴 ▶ Watch the full “Lightning in a Bottle” talk: https://www.knime.com/events/knime-data-summit-new-york Read more about the idea we call governed virality: https://www.knime.com/blog/governed-virality-why-alignment-real-speed-advantage #datagovernance #enterpriseai #aigovernance #knime
How Siemens Healthineers Centralized Data Logic into Governed Data Products
3:03
Tutorial3:03
How Siemens Healthineers Centralized Data Logic into Governed Data Products
How do you scale data access to thousands of users without losing consistency, security, or trust? At Siemens Healthineers, a governed data foundation now supports more than 6,000 users and nearly 1 million queries every month. 👨‍💻 In this segment from the KNIME Data Summit Munich, Kirk Thieme, Head of Data Product Management in Sales at Siemens Healthineers, shares how centralizing data logic into governed, reusable data products created a scalable foundation for analytics across the organization. Now, that same trusted foundation is enabling their next step: an AI sales buddy that can work with centralized skills, tools, and data. 🎥 🔴 ▶ Watch the full Data Summit talk: https://www.knime.com/events/knime-data-summit-munich Learn more about Knime Enterprise: https://www.knime.com/knime-for-enterprise #siemenshealthineers #knime #aiprojects #ai

Who uses it

Real use cases, no hype
ETL & Data Blending
Connect to databases, files, and cloud services to clean, transform, and merge data for analysis.
Predictive Analytics
Build and validate machine learning models (classification, regression) on structured data.
Automated Reporting
Generate PDF, HTML, or Excel reports from data workflows, scheduled or on-demand.
GenAI & Agent Building
Create data-aware AI agents and RAG pipelines using integrated LLM nodes.
Citizen Data Science
Enable business analysts to perform advanced analytics through a visual, code-optional interface.
Process Automation
Automate repetitive data tasks, like daily file ingestion or database updates, with scheduled workflows.
MLOps & Model Monitoring
Deploy models as data apps or REST services, with governance, versioning, and monitoring in Business Hub.
What's great
  • Truly free and open-source core platform.
  • Visual workflow builder is intuitive for beginners.
  • Massive library of 300+ data source connectors.
  • Strong enterprise governance features in paid tiers.
Technical strengths
  • Handles diverse data types (images, molecules, networks).
  • Python and R integration via managed code environments.
  • Components for reusable workflow modules.
Where it falls short
  • Free tier has severe collaboration limits.
  • Advanced features require expensive paid plans.
  • Can be slow or memory-hungry on very large datasets.
  • Vendor lock-in risk with proprietary Hub features.
Technical limitations
  • Desktop app (Eclipse-based) can feel dated.
  • Dependency management for Python/R can be tricky.
  • Learning curve for complex flow control nodes.
For technical folks

The deep-dive specs

FAQ

Includes technical Q&A
KNIME is an open-source analytics platform for creating visual data workflows. It's developed by KNIME AG, a Swiss company.

Traffic Insights

Monthly Visits

—

October 2026

Growth Rate

0%

vs last month

Dominance

0%

in Analytics

Top Country

—

Top Countries Breakdown

—

Growth Trend

Stable

Traffic has remained stable.

Honest pricing

No sneaky tiers, no “contact sales”

Here's who each plan is actually for — and where the hidden charges might hit.

Pro
Most picked
$19/mo

Individuals

  • Run & automate workflows (120 credits)
  • deploy as data apps
  • secure secrets
  • K-AI (500 interactions/month)
  • unlimited versioning
Team
$99/mo

Teams

  • All Pro features
  • plus collaborate in private spaces (3 members included)
  • centralized billing
Business Hub
Contact Sales

Enterprise

  • Automate & deploy workflows
  • collaborate with fine permissions
  • enterprise management (LDAP
  • OAuth)
  • governance
  • scalable execution
  • enterprise support
View Full Plans & Pricing on KNIME Analytics Platform

Official pricing, checkout, and plan upgrades are handled directly on knime.com.

Reviews

What the internet actually thinks

Data refreshed weekly. No paid placements.

Trustpilot
Not reviewed yet
G2
G2
Not reviewed yet
C
Capterra
Not reviewed yet
Product Hunt
Not reviewed yet
COMMUNITY COMMENTS

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