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Machine Learning · head to head

Dataiku vs GE Digital GridOS

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
GE Digital GridOS logo

GE Digital GridOS

Energy

Advanced distribution management for the modern grid

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.; GE Digital GridOS no pricing plans, tiers, or costs are published on the website
  • They diverge on capability: Dataiku covers Visual Flow, GE Digital GridOS covers ADMS.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and GE Digital GridOS actually diverge.

Attributes where Dataiku and GE Digital GridOS differ
AttributeDataikuGE Digital GridOS
Starting priceFreeOn request
Pricing modelfreemiumquote
Free tierYesNo
PlatformsLinux, Mac, Windows, WebWeb, On-premise, Api
CategoryMachine LearningEnergy
Founded20131892

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 GE Digital GridOS

  • ADMS
  • DERMS
  • Outage management
  • SCADA
  • Volt/VAR optimization
  • FLISR
  • Network modeling
  • Grid analytics

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

GE Digital GridOS

  • Grid modernizationnot Dataiku
  • DER integrationnot Dataiku
  • Outage restorationnot Dataiku
  • Grid optimizationnot Dataiku
  • Renewable integrationnot 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.

GE Digital GridOS

  • No pricing plans, tiers, or costs are published on the website
  • Requires direct contact with utility software experts for pricing inquiries

Pricing, plan by plan

Dataiku

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

GE Digital GridOS

On request
  • ADMS$undefined/custom
    • Distribution management
    • Outage management
    • SCADA integration
  • DERMS$undefined/custom
    • DER management
    • Virtual power plant
    • Grid flexibility
  • Enterprise Suite$undefined/custom
    • Full ADMS + DERMS
    • Analytics platform
    • Digital twin

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 GE Digital GridOS if

  • You need adms.
  • You work on Web, On-premise, Api.
  • You also want derms.
GE Digital GridOS review

Questions people ask

Is Dataiku or GE Digital GridOS better?
Neither clearly leads. Dataiku starts at Free and GE Digital GridOS at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or GE Digital GridOS?
Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and On request for GE Digital GridOS.
Does Dataiku or GE Digital GridOS run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. GE Digital GridOS runs on Web, On-premise, Api.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. GE Digital GridOS 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 GE Digital GridOS is typically brought in for.
What can Dataiku do that GE Digital GridOS cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. GE Digital GridOS covers ADMS, DERMS, Outage management, SCADA.

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.

GE Digital GridOS: How does GridOS publish pricing information?

GridOS does not disclose pricing on its website. Interested parties are directed to 'Connect with a utility software expert' through a contact form for pricing discussions.

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.

GE Digital GridOS: What is GridOS' licensing model?

GridOS' licensing model and pricing details are not published on publicly available pages. Custom quotes are required based on utility software implementation needs.

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.

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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