Softwr

Machine Learning · head to head

Dataiku vs KNIME

Dataiku logo

Dataiku

Machine Learning

Browser-based platform where visual data preparation and written code share one pipeline

From
Free
Rated
-
Full reviewWebsite
KNIME logo

KNIME

Machine Learning

Open source data analytics and integration platform

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dataiku visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.; KNIME the free Analytics Platform runs locally only, so anything shared or scheduled requires a paid Hub
  • They diverge on capability: Dataiku covers Visual Flow, KNIME covers Visual workflows.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and KNIME actually diverge.

Attributes where Dataiku and KNIME differ
AttributeDataikuKNIME
PlatformsLinux, Mac, Windows, WebLinux, Mac, Windows
Founded20132004

Identical on both: starting price (Free), pricing model (freemium), 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 Dataiku

  • Visual Flow
  • Visual recipes
  • Code recipes and notebooks
  • Computation pushdown
  • Automated machine learning
  • Scenarios
  • Node topology
  • Governance features

Only in KNIME

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

What people use each for

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

Dataiku

  • Organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extractsnot KNIME
  • Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot KNIME
  • Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot KNIME
  • Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot KNIME

KNIME

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

Where each one falls short

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

Dataiku

  • Visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.
  • Production requires separate automation and API nodes, each installed and licensed, so the figure quoted for building models is not the figure for running them.
  • Licensing is per user across tiers, and the lower tiers are constrained enough that occasional contributors frequently end up needing a full seat, which makes a wide rollout cost more than the initial estimate suggested.
  • A self-hosted installation needs a dedicated administrator for upgrades, connection management, permissions and node topology, so the licence is a fraction of the real cost of ownership.
  • Computation pushes down to the warehouse or Spark cluster where it is billed by that provider, so a platform sold on making analysts self-sufficient can generate a large warehouse bill that nobody attributes back to it.

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

Pricing, plan by plan

Dataiku

Free
  • Free EditionFree
    • Single user
    • Core features
  • EnterpriseFree
    • Full platform
    • Collaboration
    • MLOps

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

Which should you pick?

Choose Dataiku if

  • You need visual flow.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want visual recipes.
Dataiku review

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

Questions people ask

Is Dataiku or KNIME better?
Neither clearly leads. Dataiku starts at Free and KNIME at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or KNIME?
Dataiku starts at Free and KNIME at Free.
Does Dataiku or KNIME run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. KNIME runs on Linux, Mac, Windows.
Can I use Dataiku for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dataiku best used for?
Dataiku is most often used for organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts, regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced, pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable place, large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will accept. Of those, organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts and regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced are not what KNIME is typically brought in for.
What can Dataiku do that KNIME cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. KNIME covers Visual workflows, Data preprocessing, Machine learning, Visualization.

Answered from the vendors’ own pages

Dataiku: Is there a free version?

There is a free edition with limits on users and features, adequate for evaluation and personal work. Anything a team runs in production is a negotiated commercial agreement.

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
Dataiku: Do I have to write code to use it?

No. That is the premise. An analyst can build a complete pipeline through visual recipes, and a data scientist can write Python next to it in the same Flow.

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
Dataiku: Where does the computation actually run?

Wherever you connect it. Transformations are pushed down into the warehouse, database or Spark cluster where the data lives, which is efficient and also means the compute cost appears on that provider's bill rather than Dataiku's.

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
Dataiku: Can I export my work if we leave?

Code recipes are your code and leave with you. Visual recipes do not export as equivalent code, so the visual portion of a Flow has to be reimplemented, and that portion tends to be the majority in the projects where the platform succeeded best.

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
Dataiku: Self-hosted or cloud?

Both are offered. Self-hosting gives control over data residency and networking and requires an administrator; the managed cloud removes that work and moves the constraint to what the vendor's environment supports.

Share

Related pages

More on Dataiku

More on KNIME

Keep looking

Other head to heads