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Energy · head to head

Cognite Data Fusion vs Stem Athena

Cognite Data Fusion logo

Cognite Data Fusion

Energy

Industrial data platform that contextualises OT, IT and engineering data into an asset-centric knowledge graph

From
On request
Rated
-
Full reviewWebsite
Stem Athena logo

Stem Athena

Energy

AI-driven clean energy optimization

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Cognite Data Fusion the platform is only as good as the contextualisation work, and that mapping effort is a consulting project that regularly costs more than the first-year subscription.; Stem Athena stem's site names the product PowerTrack Optimizer, formerly Athena, so the Athena name is retired
  • They diverge on capability: Cognite Data Fusion covers Asset-centric data model, Stem Athena covers AI optimization.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Cognite Data Fusion and Stem Athena actually diverge.

Attributes where Cognite Data Fusion and Stem Athena differ
AttributeCognite Data FusionStem Athena
Pricing modelquotesubscription
PlatformsWeb, CloudWeb, Mobile, Api
FoundedUnknown2009

Identical on both: starting price (On request), free tier (No), user rating (Not yet rated), category (Energy).

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 Cognite Data Fusion

  • Asset-centric data model
  • Entity matching
  • P&ID parsing
  • 3D contextualisation
  • Cognite Atlas AI
  • Data workflows
  • Open SDKs
  • Extractors

Only in Stem Athena

  • AI optimization
  • Energy storage management
  • Demand charge reduction
  • Grid services
  • Solar integration
  • Weather forecasting
  • Performance analytics
  • Remote monitoring

What people use each for

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

Cognite Data Fusion

  • An operator that wants engineers to find the drawing, the sensor trend and the last work order for a valve from one searchnot Stem Athena
  • A company standardising asset data across sites so an analytics team can build once and deploy to many plantsnot Stem Athena
  • An upstream operator building a production-optimisation model that needs sensor data joined to equipment metadatanot Stem Athena
  • A team replacing a stalled internal data-lake project where nobody could reconstruct what the tag names meantnot Stem Athena

Stem Athena

  • Energy asset optimization and managementnot Cognite Data Fusion
  • Renewable energy integrationnot Cognite Data Fusion
  • Energy storage managementnot Cognite Data Fusion
  • Grid operations optimizationnot Cognite Data Fusion

Where each one falls short

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

Cognite Data Fusion

  • The platform is only as good as the contextualisation work, and that mapping effort is a consulting project that regularly costs more than the first-year subscription.
  • Pricing is consumption-based and unpublished, so costs move with data volume and usage patterns you cannot forecast well until a year in.
  • It does not replace your historian, your ERP or your maintenance system, so Cognite is an additional recurring cost layered on systems you still pay for.
  • The reference base and data model lean heavily towards Norwegian and wider oil, gas and process industries; discrete manufacturing fit is weaker and the local partner network thinner outside energy.
  • Getting value out requires in-house Python and data engineering skill; organisations without a data team end up dependent on Cognite professional services for every new use case.

Stem Athena

  • Stem's site names the product PowerTrack Optimizer, formerly Athena, so the Athena name is retired
  • No price, subscription fee or contract term is published anywhere on the site
  • The optimizer is one component of the wider PowerTrack suite alongside separate EMS, SCADA, Power Plant Controller and Logger products rather than a standalone licence
  • Design, procurement, commissioning and operation are sold as managed services separate from the software

Pricing, plan by plan

Cognite Data Fusion

On request
  • Cognite Data Fusion$undefined/year
    • Consumption-based pricing on data volume, compute and users
    • Available through cloud marketplaces with private offers
    • Contextualisation and onboarding quoted as a separate engagement

Stem Athena

On request
  • Commercial$undefined/custom
    • Energy storage optimization
    • Demand charge management
    • Rate optimization
  • Utility$undefined/custom
    • Grid services
    • VPP management
    • Frequency regulation
  • Enterprise$undefined/custom
    • Fleet management
    • Portfolio optimization
    • Custom integrations

Which should you pick?

Choose Cognite Data Fusion if

  • You need asset-centric data model.
  • You work on Web, Cloud.
  • You also want entity matching.
Cognite Data Fusion review

Choose Stem Athena if

  • You need ai optimization.
  • You work on Web, Mobile, Api.
  • You also want energy storage management.
Stem Athena review

Questions people ask

Is Cognite Data Fusion or Stem Athena better?
Neither clearly leads. Cognite Data Fusion starts at On request and Stem Athena at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cognite Data Fusion or Stem Athena?
Cognite Data Fusion starts at On request and Stem Athena at On request.
Does Cognite Data Fusion or Stem Athena run on more platforms?
Cognite Data Fusion runs on Web, Cloud. Stem Athena runs on Web, Mobile, Api.
What is Cognite Data Fusion best used for?
Cognite Data Fusion is most often used for an operator that wants engineers to find the drawing, the sensor trend and the last work order for a valve from one search, a company standardising asset data across sites so an analytics team can build once and deploy to many plants, an upstream operator building a production-optimisation model that needs sensor data joined to equipment metadata, a team replacing a stalled internal data-lake project where nobody could reconstruct what the tag names meant. Of those, an operator that wants engineers to find the drawing, the sensor trend and the last work order for a valve from one search and a company standardising asset data across sites so an analytics team can build once and deploy to many plants are not what Stem Athena is typically brought in for.
What can Cognite Data Fusion do that Stem Athena cannot?
Cognite Data Fusion covers Asset-centric data model, Entity matching, P&ID parsing, 3D contextualisation. Stem Athena covers AI optimization, Energy storage management, Demand charge reduction, Grid services.

Answered from the vendors’ own pages

Cognite Data Fusion: Is Cognite a historian?

No. It reads from historians such as PI System and adds context. You still need the historian underneath.

Stem Athena: How much does Stem Athena cost?

Stem does not publish pricing for Athena on its website. The company appears to use a custom enterprise pricing model. Interested customers must contact Stem directly through their website to inquire about pricing and availability.

Source
Cognite Data Fusion: How is it priced?

Consumption-based on data, compute and users, quoted per customer. Nothing is published.

Stem Athena: Does Stem offer a free trial?

The Stem website does not mention a free trial or demo option for Athena. Customers are directed to contact Stem's sales team for information about trial access or pricing.

Source
Cognite Data Fusion: How long does a deployment take?

First useful graph in a few months is realistic; full plant contextualisation across a site is typically a year or more.

Cognite Data Fusion: Can we do the contextualisation ourselves?

Technically yes, the SDKs and matching tools are open, but most customers use Cognite or a partner for the first site.

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