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Energy · head to head

Cognite Data Fusion vs Uplight

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
Uplight logo

Uplight

Energy

Customer engagement, rebate marketplaces and demand flexibility software sold to regulated utilities

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.; Uplight the product assumes a regulated utility with commission-approved programmes, so competitive retailers and aggregators find much of the reporting and measurement machinery irrelevant while still paying for it.
  • They diverge on capability: Cognite Data Fusion covers Asset-centric data model, Uplight covers Energy marketplace.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

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

Attributes where Cognite Data Fusion and Uplight differ
AttributeCognite Data FusionUplight
PlatformsWeb, CloudWeb, iOS, Android, API

Identical on both: starting price (On request), pricing model (quote), 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 Uplight

  • Energy marketplace
  • Personalised recommendations
  • Rates engagement
  • Demand response
  • Distributed energy resource management
  • Programme reporting
  • Home energy reports
  • OEM and device partnerships

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 Uplight
  • A company standardising asset data across sites so an analytics team can build once and deploy to many plantsnot Uplight
  • An upstream operator building a production-optimisation model that needs sensor data joined to equipment metadatanot Uplight
  • A team replacing a stalled internal data-lake project where nobody could reconstruct what the tag names meantnot Uplight

Uplight

  • A regulated utility that must deliver an approved energy efficiency programme and evidence the savings to its commissionnot Cognite Data Fusion
  • A utility launching a residential demand response programme built on customer-owned thermostats and batteriesnot Cognite Data Fusion
  • A utility moving customers onto time-of-use tariffs that needs enrolment journeys rather than a billing change alonenot Cognite Data Fusion
  • A utility that wants rebates applied at the point of purchase instead of processing claim forms after the factnot 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.

Uplight

  • The product assumes a regulated utility with commission-approved programmes, so competitive retailers and aggregators find much of the reporting and measurement machinery irrelevant while still paying for it.
  • Procurement runs through long RFPs tied to rate cases and programme approvals, so implementation dates are set by a regulator rather than by the utility or the vendor and slip when filings slip.
  • The investor group of Schneider Electric, AES and Octopus Energy Group is made up of active energy market participants, which is a governance question a utility should raise in diligence rather than discover later.
  • The platform spans engagement, marketplace and demand management, and those capabilities were built or acquired separately, so a buyer taking one module gets less of the integration benefit than the platform story implies.
  • The reference base and product depth are strongest in North America, so a European or Asia-Pacific utility gets fewer comparable deployments and less functionality built around local market rules.

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

Uplight

On request
  • Uplight platform$undefined/year
    • Quoted per utility programme by customer count and modules
    • Frequently structured around approved programme budgets and performance targets
    • Marketplace economics include product fulfilment and rebate handling

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 Uplight if

  • You need energy marketplace.
  • You work on Web, iOS, Android, API.
  • You also want personalised recommendations.
Uplight review

Questions people ask

Is Cognite Data Fusion or Uplight better?
Neither clearly leads. Cognite Data Fusion starts at On request and Uplight 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 Uplight?
Cognite Data Fusion starts at On request and Uplight at On request.
Does Cognite Data Fusion or Uplight run on more platforms?
Cognite Data Fusion runs on Web, Cloud. Uplight runs on Web, iOS, Android, 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 Uplight is typically brought in for.
What can Cognite Data Fusion do that Uplight cannot?
Cognite Data Fusion covers Asset-centric data model, Entity matching, P&ID parsing, 3D contextualisation. Uplight covers Energy marketplace, Personalised recommendations, Rates engagement, Demand response.

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.

Uplight: Who owns Uplight?

It is privately held and backed by Schneider Electric, AES Corporation and Octopus Energy Group.

Cognite Data Fusion: How is it priced?

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

Uplight: Can a competitive energy retailer use it?

It can, but the product is designed around regulated programme delivery and measurement, so a retailer pays for machinery it does not need.

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.

Uplight: Does Uplight do demand response as well as efficiency?

Yes. It acquired the AutoGrid distributed energy resource platform from Schneider Electric in 2024, which added device control and dispatch to the engagement business.

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.

Uplight: Is pricing published?

No. Deals are quoted per programme and usually sized against an approved programme budget.

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