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Machine Learning · head to head

Dataiku vs IBM SPSS

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
IBM SPSS logo

IBM SPSS

Machine Learning

Statistical analysis software for data science

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.; IBM SPSS add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
  • They diverge on capability: Dataiku covers Visual Flow, IBM SPSS covers Statistical analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and IBM SPSS actually diverge.

Attributes where Dataiku and IBM SPSS differ
AttributeDataikuIBM SPSS
Pricing modelfreemiumsubscription
PlatformsLinux, Mac, Windows, WebLinux, Mac, Windows
Founded20131911

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 Dataiku

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

Only in IBM SPSS

  • Statistical analysis
  • Predictive modeling
  • Data visualization
  • Survey analysis
  • Decision trees
  • Python
  • R
  • Excel

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 IBM SPSS
  • Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot IBM SPSS
  • Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot IBM SPSS
  • Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot IBM SPSS

IBM SPSS

  • Statistical testing and regression analysis for academic and market researchnot Dataiku
  • Predictive modelling and forecasting without writing codenot 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.

IBM SPSS

  • Add-on packages are priced separately from the base subscription, and the promotional 45% discount on them excludes renewals
  • Subscription cost renews at the then current price at the end of the first year, so the advertised rate applies to the first term only
  • Prices shown are described by IBM as indicative, vary by country and exclude applicable taxes and duties
  • Extended access periods of 12 months or more are handled as tailored pricing rather than a published rate
  • Advanced statistics, custom tables, decision trees and forecasting are separate add-ons rather than part of the base product

Pricing, plan by plan

Dataiku

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

IBM SPSS

Free
  • TrialFree
    • 14-day trial
    • Full features
  • Base$99/month
    • Core statistics
    • Data management

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 IBM SPSS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want predictive modeling.
IBM SPSS review

Questions people ask

Is Dataiku or IBM SPSS better?
Neither clearly leads. Dataiku starts at Free and IBM SPSS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or IBM SPSS?
Dataiku starts at Free and IBM SPSS at Free.
Does Dataiku or IBM SPSS run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. IBM SPSS 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 IBM SPSS is typically brought in for.
What can Dataiku do that IBM SPSS cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. IBM SPSS covers Statistical analysis, Predictive modeling, Data visualization, Survey analysis.

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.

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.

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.

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.

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.

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