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Energy · head to head

Cognite Data Fusion vs Lambda Labs

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
Lambda Labs logo

Lambda Labs

AI

GPU cloud for deep learning

From
$1.1/per-hour
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.; Lambda Labs on demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
  • They diverge on capability: Cognite Data Fusion covers Asset-centric data model, Lambda Labs covers NVIDIA GPUs.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

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

Attributes where Cognite Data Fusion and Lambda Labs differ
AttributeCognite Data FusionLambda Labs
Starting priceOn request$1.1/per-hour
Pricing modelquoteusage-based
PlatformsWeb, CloudCloud
CategoryEnergyAI
FoundedUnknown2012

Identical on both: free tier (No), 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 Cognite Data Fusion

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

Only in Lambda Labs

  • NVIDIA GPUs
  • Pre-installed frameworks
  • Persistent storage
  • SSH access
  • JupyterLab
  • VSCode
  • SSH
  • Cloud support

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

Lambda Labs

  • Renting GPU instances for model training and inferencenot Cognite Data Fusion
  • Short term access to high memory accelerators without buying hardwarenot 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.

Lambda Labs

  • On demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
  • H100 pricing varies within a band, at $3.99 to $4.29 an hour per GPU, so the rate is not fixed
  • Reserved capacity is arranged by contacting the team rather than self serve
  • Prices are quoted before applicable tax

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

Lambda Labs

$1.1/per-hour
  • On-Demand$1.1/per-hour
    • A10 GPU
    • Instant availability
  • ReservedFree
    • Volume discounts
    • Guaranteed capacity

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 Lambda Labs if

  • You need nvidia gpus.
  • You work on Cloud.
  • You also want pre-installed frameworks.
Lambda Labs review

Questions people ask

Is Cognite Data Fusion or Lambda Labs better?
Neither clearly leads. Cognite Data Fusion starts at On request and Lambda Labs at $1.1/per-hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cognite Data Fusion or Lambda Labs?
Cognite Data Fusion starts at On request and Lambda Labs at $1.1/per-hour.
Does Cognite Data Fusion or Lambda Labs run on more platforms?
Cognite Data Fusion runs on Web, Cloud. Lambda Labs runs on Cloud.
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 Lambda Labs is typically brought in for.
What can Cognite Data Fusion do that Lambda Labs cannot?
Cognite Data Fusion covers Asset-centric data model, Entity matching, P&ID parsing, 3D contextualisation. Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, Persistent storage, SSH access.

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.

Lambda Labs: What does Lambda Labs GPU pricing depend on?

Lambda Labs pricing depends on the GPU model (H100, B200, A100, V100, etc.), cluster size, and contract length. For example, a 16-GPU H100 cluster costs $6.16/GPU/hour for 2 weeks to 1 year, while A100 GPUs are $1.99-$2.79/GPU/hour.

Source
Cognite Data Fusion: How is it priced?

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

Lambda Labs: Are there volume discounts for larger GPU clusters?

Yes. Pricing decreases with larger cluster orders. For example, NVIDIA H100 clusters cost $6.16/GPU/hour for 16 GPUs, $5.85/GPU/hour for 64 GPUs, and $5.54/GPU/hour for 256 GPUs (all for 2 weeks to 1 year terms).

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.

Lambda Labs: Can I get custom pricing for a long-term GPU contract?

Yes. For cluster orders of 16+ GPUs with 1-year or longer contracts, Lambda Labs offers custom pricing. Contact their sales team to request a quote.

Source
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.

Lambda Labs: What additional costs should I expect beyond the hourly GPU rate?

All listed prices are plus applicable sales tax, VAT, or GST depending on your location.

Source
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