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Machine Learning · head to head

KNIME vs Kubeflow

KNIME logo

KNIME

Machine Learning

Open source data analytics and integration platform

From
Free
Rated
-
Full reviewWebsite
Kubeflow logo

Kubeflow

Machine Learning

Machine learning toolkit for Kubernetes

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub; Kubeflow complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
  • They diverge on capability: KNIME covers Visual workflows, Kubeflow covers ML pipelines.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which KNIME and Kubeflow actually diverge.

Attributes where KNIME and Kubeflow differ
AttributeKNIMEKubeflow
Pricing modelfreemiumUnknown
PlatformsLinux, Mac, WindowsKubernetes
Founded20042017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in KNIME

  • Visual workflows
  • Data preprocessing
  • Machine learning
  • Visualization
  • Reporting
  • Python
  • R
  • Spark

Only in Kubeflow

  • ML pipelines
  • Training operators
  • Model serving
  • Jupyter notebooks
  • Hyperparameter tuning
  • Kubernetes
  • PyTorch
  • XGBoost

Both cover

  • TensorFlow
  • Linux support

What people use each for

The jobs each tool is most often brought in to do.

KNIME

  • Data science and machine learning workflowsnot Kubeflow
  • ETL and data pipeline automationnot Kubeflow
  • Predictive analytics and modelingnot Kubeflow

Kubeflow

  • Machine learningnot KNIME
  • Data analysisnot KNIME
  • Model trainingnot KNIME
  • Predictive analyticsnot KNIME

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

KNIME

  • The free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
  • The free AI assistant is limited to 20 interactions a month
  • Paid workflow runtime is metered in credits, with 120 included on Pro and overage at $0.025 per vCore minute
  • The Team plan at $99 a month includes 3 members, with additional seats at $49 a month each
  • Business Hub pricing is on request, and its tiers are capped at 4, 8 and 16 vCores with 5, 5 and 20 users

Kubeflow

  • Complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
  • Resource-intensive infrastructure with minimal installs consuming significant CPU and memory
  • Limited multi-tenancy support and multi-cloud setup leaves users largely on their own
  • No native CI/CD integration, requiring custom glue code for versioning and automated deployments
  • Debugging jobs and monitoring workloads often requires dropping down into raw Kubernetes commands

Pricing, plan by plan

KNIME

Free
  • Analytics PlatformFree
    • 300+ data sources
    • Unlimited local processing
    • K-AI assistant (20 interactions/month)
  • Pro$19/month
    • 120 workflow runtime credits
    • Data app deployment
    • K-AI (500 interactions/month)
  • Team$99/month
    • All Pro features
    • Collaboration spaces for up to 3 team members
    • Additional members: $49/month each
  • Business Hub$null/month
    • Enterprise automation and governance
    • LDAP/OAuth authentication
    • Staged deployment

Kubeflow

Free

No published plan breakdown. See the Kubeflow review.

Which should you pick?

Choose KNIME if

  • You need visual workflows.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data preprocessing.
KNIME review

Choose Kubeflow if

  • You need ml pipelines.
  • You want to start without paying.
  • You work on Kubernetes.
  • You also want training operators.
Kubeflow review

Questions people ask

Is KNIME or Kubeflow better?
Neither clearly leads. KNIME starts at Free and Kubeflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, KNIME or Kubeflow?
KNIME starts at Free and Kubeflow at Free.
Does KNIME or Kubeflow run on more platforms?
KNIME runs on Linux, Mac, Windows. Kubeflow runs on Kubernetes.
Can I use KNIME for free?
Both have a free tier, so you can try either at no cost before committing.
What is KNIME best used for?
KNIME is most often used for data science and machine learning workflows, etl and data pipeline automation, predictive analytics and modeling. Of those, data science and machine learning workflows and etl and data pipeline automation are not what Kubeflow is typically brought in for.
What can KNIME do that Kubeflow cannot?
KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization. Kubeflow covers ML pipelines, Training operators, Model serving, Jupyter notebooks. Both handle TensorFlow, Linux support.

Answered from the vendors’ own pages

KNIME: Is KNIME free?

Yes, KNIME Analytics Platform is free with 300+ data sources, unlimited local processing, and 20 K-AI assistant interactions per month.

Source
Kubeflow: Is Kubeflow free to use?

Yes, Kubeflow is free and open-source under Apache License 2.0. However, you pay for the underlying Kubernetes infrastructure, which typically costs $500 to $5,000 per month depending on scale and cloud provider.

Source
KNIME: What do KNIME paid plans cost?

Pro plan starts at $19/month with 120 runtime credits. Team plan starts at $99/month for up to 3 members, with additional members at $49/month each.

Source
Kubeflow: Do I need Kubernetes expertise to use Kubeflow?

Kubeflow requires significant Kubernetes and DevOps expertise. The installation deploys dozens of services and CRDs, often requiring manual configuration and troubleshooting. Data scientists typically need to convert scripts to containerized components.

Source
KNIME: What is KNIME's runtime credit system?

Pro and Team plans include runtime credits for workflow execution. Additional runtime beyond included credits costs $0.025 per vCore minute.

Source
Kubeflow: What platforms can Kubeflow run on?

Kubeflow runs on any Kubernetes-compliant cluster, including on-premise, AWS, Azure, Google Cloud, and hybrid environments. This multi-cloud portability is one of its key advantages over managed alternatives.

Source
KNIME: Does KNIME offer enterprise pricing?

Yes, Business Hub is available for enterprises needing automation, governance, LDAP/OAuth auth, and dedicated resources. Pricing available on request.

Source
Kubeflow: How does Kubeflow compare to managed services like SageMaker?

Kubeflow offers multi-cloud portability and lower long-term costs but requires more operational overhead. SageMaker provides a fully managed experience with better UI and less infrastructure work, but creates vendor lock-in to AWS.

Source
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