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Energy · head to head

Cognite Data Fusion vs iHawk by Cyberhawk

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
iHawk by Cyberhawk logo

iHawk by Cyberhawk

Energy

Asset inspection data platform sold by a drone inspection service company, not standalone software

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.; iHawk by Cyberhawk cyberhawk's business is inspection services, so the platform is normally sold as part of a capture contract and the software line item cannot be compared cleanly against standalone asset inspection platforms
  • They diverge on capability: Cognite Data Fusion covers Asset-centric data model, iHawk by Cyberhawk covers Visual data management.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Cognite Data Fusion and iHawk by Cyberhawk actually diverge.

Attributes where Cognite Data Fusion and iHawk by Cyberhawk differ
AttributeCognite Data FusioniHawk by Cyberhawk
PlatformsWeb, CloudWeb

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 iHawk by Cyberhawk

  • Visual data management
  • Defect tagging and tracking
  • Visualive AI review
  • Geospatial layers
  • Asset hierarchy
  • Progress monitoring
  • Reporting and export

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

iHawk by Cyberhawk

  • A transmission operator inspecting several thousand towers annually that needs defect history per structure rather than a folder of photographs per campaignnot Cognite Data Fusion
  • An offshore operator that wants flare tip and structural inspection imagery held against the same asset tags used in its maintenance systemnot Cognite Data Fusion
  • A capital project owner tracking construction progress from repeated aerial capture over a two year buildnot Cognite Data Fusion
  • A utility responding to a regulator that requires evidence of condition assessment across a defined asset populationnot 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.

iHawk by Cyberhawk

  • Cyberhawk's business is inspection services, so the platform is normally sold as part of a capture contract and the software line item cannot be compared cleanly against standalone asset inspection platforms
  • Nothing is published about price, and because contracts bundle flights, processing and platform access, the recurring cost after the inspection campaign ends is often not clear at signature
  • The value of the platform grows with the length of the historical series held in it, which makes switching increasingly expensive over time and gives the vendor leverage at renewal
  • It is a review and management platform rather than an enterprise asset management system, so defect findings still need to reach SAP or Maximo to become work orders, and that integration is a project in its own right
  • Automated defect detection reduces review effort but does not remove the need for qualified inspection engineers to sign off findings, so headcount savings are smaller than a technology-led business case usually assumes

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

iHawk by Cyberhawk

On request
  • iHawk platform$undefined/year
    • Usually contracted together with Cyberhawk inspection services
    • Priced by asset count, data volume and inspection programme scope
    • Standalone platform licensing available on request but not the standard route

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 iHawk by Cyberhawk if

  • You need visual data management.
  • You also want defect tagging and tracking.
iHawk by Cyberhawk review

Questions people ask

Is Cognite Data Fusion or iHawk by Cyberhawk better?
Neither clearly leads. Cognite Data Fusion starts at On request and iHawk by Cyberhawk 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 iHawk by Cyberhawk?
Cognite Data Fusion starts at On request and iHawk by Cyberhawk at On request.
Does Cognite Data Fusion or iHawk by Cyberhawk run on more platforms?
Cognite Data Fusion runs on Web, Cloud. iHawk by Cyberhawk runs on Web.
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 iHawk by Cyberhawk is typically brought in for.
What can Cognite Data Fusion do that iHawk by Cyberhawk cannot?
Cognite Data Fusion covers Asset-centric data model, Entity matching, P&ID parsing, 3D contextualisation. iHawk by Cyberhawk covers Visual data management, Defect tagging and tracking, Visualive AI review, Geospatial layers.

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.

iHawk by Cyberhawk: Can I buy iHawk without Cyberhawk's inspection services?

Ask explicitly. The company positions the platform as enterprise software, but its normal route to market is bundled with data capture, so standalone terms are negotiated rather than listed.

Cognite Data Fusion: How is it priced?

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

iHawk by Cyberhawk: Who owns the inspection data?

That is contract-specific and should be settled before signature, including what format you receive on exit and whether historical defect tagging comes with you.

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.

iHawk by Cyberhawk: What does it cost?

Not published. Expect pricing driven by asset count, data volume and the scope of the inspection programme.

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.

iHawk by Cyberhawk: Does it replace an asset management system?

No. It manages inspection data and findings. Work orders and maintenance planning stay in SAP, Maximo or your equivalent.

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