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Business Intelligence · head to head

Anaplan vs Dataiku

Anaplan logo

Anaplan

Business Intelligence

Connected planning platform with an in-memory calculation engine for large multidimensional models

From
On request
Rated
-
Full reviewWebsite
Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Dataiku has a free tier, so it costs nothing to try first.
  • Each has a real cost: Anaplan workspace is licensed by memory consumed, so a model that grows as the business adds SKUs, regions or scenarios generates a bill increase without a single new user being added, and teams end up optimising models for licence cost rather than clarity.; 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.
  • They diverge on capability: Anaplan covers Hyperblock calculation engine, Dataiku covers Visual Flow.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Anaplan and Dataiku actually diverge.

Attributes where Anaplan and Dataiku differ
AttributeAnaplanDataiku
Starting priceOn requestFree
Pricing modelquotefreemium
Free tierNoYes
PlatformsWeb, iOSLinux, Mac, Windows, Web
CategoryBusiness IntelligenceMachine Learning
FoundedUnknown2013

Identical on both: user rating (Not yet rated).

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 Anaplan

  • Hyperblock calculation engine
  • Connected planning
  • Scenario and versioning
  • Model builder
  • Anaplan PlanIQ
  • Workflow and approvals
  • Application lifecycle management
  • Data integration

Only in Dataiku

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

What people use each for

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

Anaplan

  • Sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediatelynot Dataiku
  • Demand and supply planning at SKU and location level for a manufacturer with tens of thousands of itemsnot Dataiku
  • Workforce planning that ties headcount, cost and capacity to a revenue plan across dozens of business unitsnot Dataiku
  • Replacing a spreadsheet estate where the master planning model has become too large and too fragile for Excel to open reliablynot Dataiku

Dataiku

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

Where each one falls short

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

Anaplan

  • Workspace is licensed by memory consumed, so a model that grows as the business adds SKUs, regions or scenarios generates a bill increase without a single new user being added, and teams end up optimising models for licence cost rather than clarity.
  • Model building requires certified Anaplan modellers using a proprietary formula language, and the labour market for that skill is small, so most customers stay dependent on a systems integrator long after go-live.
  • Thoma Bravo took the company private in 2022 in a $10.7bn deal, and customers have since reported firmer renewal terms; a private-equity owner optimising for cash flow is a real factor in a multi-year planning contract.
  • Native reporting and visualisation are weak for anything beyond planning grids, so most customers push data out to Power BI or Tableau for executive reporting, adding another tool and another latency point.
  • Implementations are long. A connected planning programme across finance and supply chain routinely runs six to eighteen months before the first production plan, which is difficult to justify when the business wants a forecast this quarter.

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.

Pricing, plan by plan

Anaplan

On request
  • Anaplan$undefined/year
    • Licensed by user tier and by workspace capacity
    • Workspace charged on memory consumed by models, independent of user count
    • Multi-year enterprise agreements are the norm

Dataiku

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

Which should you pick?

Choose Anaplan if

  • You need hyperblock calculation engine.
  • You work on Web, iOS.
  • You also want connected planning.
Anaplan review

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

Questions people ask

Is Anaplan or Dataiku better?
Neither clearly leads. Anaplan starts at On request and Dataiku at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anaplan or Dataiku?
Dataiku has a free tier; the other does not. Paid plans start at On request for Anaplan and Free for Dataiku.
Does Anaplan or Dataiku run on more platforms?
Anaplan runs on Web, iOS. Dataiku runs on Linux, Mac, Windows, Web.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. Anaplan starts at On request.
What is Anaplan best used for?
Anaplan is most often used for sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediately, demand and supply planning at sku and location level for a manufacturer with tens of thousands of items, workforce planning that ties headcount, cost and capacity to a revenue plan across dozens of business units, replacing a spreadsheet estate where the master planning model has become too large and too fragile for excel to open reliably. Of those, sales territory and quota planning across thousands of reps where a change to segmentation must reflow quota immediately and demand and supply planning at sku and location level for a manufacturer with tens of thousands of items are not what Dataiku is typically brought in for.
What can Anaplan do that Dataiku cannot?
Anaplan covers Hyperblock calculation engine, Connected planning, Scenario and versioning, Model builder. Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown.

Answered from the vendors’ own pages

Anaplan: Why is Anaplan expensive even when user counts are low?

Because workspace is licensed on the memory your models consume as well as on users. Large models cost money regardless of how many people log in.

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.

Anaplan: Do we need a systems integrator?

Almost always for the first implementation. The proprietary modelling language and the scale of typical models make an experienced partner or an internal certified team effectively mandatory.

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.

Anaplan: Who owns Anaplan?

Thoma Bravo, which took it private in 2022 for $10.7bn.

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.

Anaplan: Can it replace our BI tool?

No. It is a planning and calculation platform; most customers still export to Power BI or Tableau for reporting and dashboards.

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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