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Machine Learning · head to head

Dataiku vs Quantum Metric

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
Quantum Metric logo

Quantum Metric

Business Intelligence

Continuous product design platform

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Dataiku has a free tier, so it costs nothing to try first.
  • 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.; Quantum Metric only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum
  • They diverge on capability: Dataiku covers Visual Flow, Quantum Metric covers Session Replay.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and Quantum Metric actually diverge.

Attributes where Dataiku and Quantum Metric differ
AttributeDataikuQuantum Metric
Starting priceFreeOn request
Pricing modelfreemiumsubscription
Free tierYesNo
PlatformsLinux, Mac, Windows, WebWeb, Mobile
CategoryMachine LearningBusiness Intelligence
Founded20132015

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 Dataiku

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

Only in Quantum Metric

  • Session Replay
  • Opportunity Analysis
  • Anomaly Detection
  • Real-time Alerts
  • Impact Scoring
  • Adobe Analytics
  • Google Analytics
  • Salesforce

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

Quantum Metric

  • Session replay and digital experience analytics for large web and mobile propertiesnot Dataiku
  • Quantifying friction and conversion loss in checkout and signup flowsnot Dataiku
  • Streaming behavioural insights into a data warehousenot 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.

Quantum Metric

  • Only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum
  • The page states plans are built around your business, with the only routes being a personalised discussion, a live demo or product tours
  • There is no self-serve tier, free plan or trial published

Pricing, plan by plan

Dataiku

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

Quantum Metric

On request
  • CustomFree
    • Full Platform
    • Real-time Analytics
    • Enterprise Support

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 Quantum Metric if

  • You need session replay.
  • You work on Web, Mobile.
  • You also want opportunity analysis.
Quantum Metric review

Questions people ask

Is Dataiku or Quantum Metric better?
Neither clearly leads. Dataiku starts at Free and Quantum Metric at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Quantum Metric?
Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and On request for Quantum Metric.
Does Dataiku or Quantum Metric run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Quantum Metric runs on Web, Mobile.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. Quantum Metric starts at On request.
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 Quantum Metric is typically brought in for.
What can Dataiku do that Quantum Metric cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. Quantum Metric covers Session Replay, Opportunity Analysis, Anomaly Detection, Real-time Alerts.

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.

Quantum Metric: How much does Quantum Metric cost?

Quantum Metric uses custom pricing based on annual session volume, number of digital properties monitored, and product add-ons. Exact costs require contacting the sales team.

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.

Quantum Metric: Does Quantum Metric offer a free trial?

The pricing page does not mention a free trial option. Interested parties must request a demo to discuss pricing and obtain a custom quote.

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.

Quantum Metric: What factors affect Quantum Metric pricing?

Pricing scales with digital properties (websites and applications monitored), session volume (data collected and analyzed), and customer success tier selected. Add-on products like employee experience, data enrichment, and data streaming have separate pricing considerations.

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.

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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