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Machine Learning · head to head

Dataiku vs IBM QRadar

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
IBM QRadar logo

IBM QRadar

Cybersecurity

Enterprise SIEM licensed by events per second, whose cloud business IBM sold to Palo Alto Networks in 2024.

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.; IBM QRadar iBM sold the QRadar SaaS business to Palo Alto Networks in 2024 and those customers are being moved to Cortex XSIAM, so anyone buying today is choosing an on-premises product whose vendor has publicly moved the cloud future to a competitor, and the support horizon becomes a contract negotiation rather than an assumption.
  • They diverge on capability: Dataiku covers Visual Flow, IBM QRadar covers Offence model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Dataiku and IBM QRadar differ
AttributeDataikuIBM QRadar
Starting priceFreeOn request
Pricing modelfreemiumsubscription
Free tierYesNo
PlatformsLinux, Mac, Windows, WebWeb, Api
CategoryMachine LearningCybersecurity
Founded20131911

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 IBM QRadar

  • Offence model
  • Network flow analysis
  • Device Support Modules
  • Ariel query language
  • Rules and building blocks
  • Deployment topology
  • App Exchange
  • Use Case Manager

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

IBM QRadar

  • A regulated enterprise that must keep log data on premises or in a specific jurisdiction and cannot use a shared SaaS SIEMnot Dataiku
  • A SOC that wants log correlation and network flow analysis in one platform rather than buying an NDR product separatelynot Dataiku
  • An existing QRadar estate deciding whether to stay on premises or accept the migration path to a different vendor's platformnot Dataiku
  • Compliance-driven log retention and reporting where the audit requirement is specific about collection, retention and reportingnot 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 QRadar

  • IBM sold the QRadar SaaS business to Palo Alto Networks in 2024 and those customers are being moved to Cortex XSIAM, so anyone buying today is choosing an on-premises product whose vendor has publicly moved the cloud future to a competitor, and the support horizon becomes a contract negotiation rather than an assumption.
  • Licensing is by events per second and flows per minute, so every additional log source raises the cost directly and teams routinely exclude verbose sources such as DNS, proxy, endpoint and cloud audit logs to stay under the licence, which strips out exactly the data an investigation later needs.
  • It needs a dedicated operator: rule tuning, parser work and offence triage are continuous jobs, and an organisation that deploys QRadar without at least one named engineer accumulates thousands of unreviewed offences and a false sense of coverage.
  • A log source without a matching Device Support Module arrives unparsed, and writing a custom parser with regular expressions against an unfamiliar payload format is specialist work that can take days per source, which quietly determines which systems ever get monitored.
  • On-premises capacity is planned across consoles, processors, collectors and data nodes, so outgrowing the sizing means procuring and racking more appliances rather than changing a subscription tier, and growth becomes a purchasing cycle measured in months.

Pricing, plan by plan

Dataiku

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

IBM QRadar

On request
  • QRadar SIEMFree
    • Event and flow processing
    • Offense management
    • Threat intelligence
  • QRadar CloudFree
    • Cloud-native deployment
    • Elastic scaling
    • Managed infrastructure
  • QRadar SuiteFree
    • SIEM + SOAR + XDR
    • Unified analyst experience
    • Federated search

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 QRadar if

  • You need offence model.
  • You work on Web, Api.
  • You also want network flow analysis.
IBM QRadar review

Questions people ask

Is Dataiku or IBM QRadar better?
Neither clearly leads. Dataiku starts at Free and IBM QRadar at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or IBM QRadar?
Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and On request for IBM QRadar.
Does Dataiku or IBM QRadar run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. IBM QRadar runs on Web, Api.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. IBM QRadar 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 IBM QRadar is typically brought in for.
What can Dataiku do that IBM QRadar cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. IBM QRadar covers Offence model, Network flow analysis, Device Support Modules, Ariel query language.

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.

IBM QRadar: Who owns QRadar now?

It is split. IBM sold the QRadar SaaS assets to Palo Alto Networks in a deal announced in May 2024 and closed that September, and those customers are being migrated to Cortex XSIAM. IBM retains and supports the on-premises product.

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.

IBM QRadar: Is QRadar being discontinued?

IBM has committed to continuing support for on-premises customers, including security updates, while offering migration assistance. The cloud product's future belongs to Palo Alto. If you are signing a multi-year term, get the support horizon written into the contract.

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.

IBM QRadar: How is it licensed?

By events per second for logs and flows per minute for network data, with the software or appliance sized to that rate. Add-on modules in the suite are licensed separately.

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.

IBM QRadar: What is an offence?

QRadar's term for a correlated case. Rules group related events and flows against a common indicator such as a host or user, so an analyst reviews one offence rather than the hundreds of events behind it.

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.

IBM QRadar: Do I need a full-time engineer?

In practice yes for anything beyond a small deployment. Parser development, rule tuning and offence triage do not stop, and the most common failure mode is a well-installed QRadar that nobody has tuned since go-live.

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