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Machine Learning · head to head

Dataiku vs EnergyCAP

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
EnergyCAP logo

EnergyCAP

Energy

Utility bill and energy management software

From
$1000/month
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.; EnergyCAP priced per meter per year, so cost scales with how many utility connection points exist rather than with users or sites
  • They diverge on capability: Dataiku covers Visual Flow, EnergyCAP covers Utility bill management.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and EnergyCAP actually diverge.

Attributes where Dataiku and EnergyCAP differ
AttributeDataikuEnergyCAP
Starting priceFree$1000/month
Pricing modelfreemiumsubscription
Free tierYesNo
PlatformsLinux, Mac, Windows, WebWeb, Api
CategoryMachine LearningEnergy
Founded20131980

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 EnergyCAP

  • Utility bill management
  • Energy accounting
  • Cost allocation
  • Sustainability reporting
  • Weather normalization
  • Rate analysis
  • Budgeting
  • Benchmarking

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

EnergyCAP

  • Tracking utility bills and energy consumption across a property portfolionot Dataiku
  • Reporting on energy spend and emissions for an organisationnot 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.

EnergyCAP

  • Priced per meter per year, so cost scales with how many utility connection points exist rather than with users or sites
  • No figure is published at any level, and every package is quoted by sales
  • Emissions, interval data, bill capture and bill pay are separately priced add ons rather than part of the core platform

Pricing, plan by plan

Dataiku

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

EnergyCAP

$1000/month
  • Essential$1000/month
    • Utility bill management
    • Energy tracking
    • Basic reporting
  • Professional$2500/month
    • Advanced analytics
    • Sustainability reporting
    • Budgeting tools
  • Enterprise$undefined/month
    • Unlimited users
    • Custom integrations
    • API access

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 EnergyCAP if

  • You need utility bill management.
  • You work on Web, Api.
  • You also want energy accounting.
EnergyCAP review

Questions people ask

Is Dataiku or EnergyCAP better?
Neither clearly leads. Dataiku starts at Free and EnergyCAP at $1000/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or EnergyCAP?
Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and $1000/month for EnergyCAP.
Does Dataiku or EnergyCAP run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. EnergyCAP runs on Web, Api.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. EnergyCAP starts at $1000/month.
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 EnergyCAP is typically brought in for.
What can Dataiku do that EnergyCAP cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. EnergyCAP covers Utility bill management, Energy accounting, Cost allocation, Sustainability reporting.

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.

EnergyCAP: What is EnergyCAP's pricing model?

EnergyCAP pricing is based per meter per year. The company allows customers to customize their package by adding premium features such as emissions tracking, interval data analytics, finance modules, bill capture, and bill pay services based on business needs.

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.

EnergyCAP: How much does EnergyCAP cost?

EnergyCAP does not publish specific pricing amounts. Customers must contact sales for a customized quote based on their meter count and selected features.

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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