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Energy · head to head

Cognite Data Fusion vs Snowflake

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
Snowflake logo

Snowflake

Machine Learning

The AI Data Cloud for enterprise data warehousing

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Snowflake has a free tier, so it costs nothing to try first.
  • 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.; Snowflake no flat subscription price is published - cost varies by edition, cloud provider, and region and requires a separate calculator or credit-consumption table
  • They diverge on capability: Cognite Data Fusion covers Asset-centric data model, Snowflake covers Separated Compute/Storage.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

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

Attributes where Cognite Data Fusion and Snowflake differ
AttributeCognite Data FusionSnowflake
Starting priceOn requestFree
Pricing modelquoteUnknown
Free tierNoYes
PlatformsWeb, CloudWeb, API
CategoryEnergyMachine Learning
FoundedUnknown2012

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 Cognite Data Fusion

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

Only in Snowflake

  • Separated Compute/Storage
  • Near-zero Maintenance
  • Data Sharing
  • Time Travel
  • Cloning
  • Multi-cluster Warehouse
  • Semi-structured Data
  • dbt

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

Snowflake

  • Cloud data warehousing and SQL analyticsnot Cognite Data Fusion
  • Data engineering and ELT pipelinesnot Cognite Data Fusion
  • Data sharing and marketplacenot Cognite Data Fusion
  • AI/ML workloads via Snowpark and Cortexnot Cognite Data Fusion
  • BI backend for tools such as Tableau and Power BInot 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.

Snowflake

  • No flat subscription price is published - cost varies by edition, cloud provider, and region and requires a separate calculator or credit-consumption table
  • Free trial is capped at $400 in credits or 30 days, whichever comes first, not a perpetual free tier
  • During the trial, certain features (external network access, hybrid tables, Openflow) are capped at 10 credits/day until a payment method is added
  • Total cost combines compute credits, storage, and data transfer billed separately

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

Snowflake

Free
  • Standard$undefined/mo
    • Consumption-based, per-credit pricing
  • Enterprise$undefined/mo
    • Consumption-based, per-credit pricing
  • Business Critical$undefined/mo
    • Consumption-based, per-credit pricing
  • Virtual Private Snowflake$undefined/mo
    • Consumption-based, per-credit pricing

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 Snowflake if

  • You need separated compute/storage.
  • You want to start without paying.
  • You work on Web, API.
  • You also want near-zero maintenance.
Snowflake review

Questions people ask

Is Cognite Data Fusion or Snowflake better?
Neither clearly leads. Cognite Data Fusion starts at On request and Snowflake at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cognite Data Fusion or Snowflake?
Snowflake has a free tier; the other does not. Paid plans start at On request for Cognite Data Fusion and Free for Snowflake.
Does Cognite Data Fusion or Snowflake run on more platforms?
Cognite Data Fusion runs on Web, Cloud. Snowflake runs on Web, API.
Can I use Snowflake for free?
Yes. Snowflake has a free tier, so you can try it without paying. Cognite Data Fusion starts at On request.
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 Snowflake is typically brought in for.
What can Cognite Data Fusion do that Snowflake cannot?
Cognite Data Fusion covers Asset-centric data model, Entity matching, P&ID parsing, 3D contextualisation. Snowflake covers Separated Compute/Storage, Near-zero Maintenance, Data Sharing, Time Travel.

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.

Snowflake: How is Snowflake priced?

Snowflake uses a consumption based model. Compute is billed in credits and storage is charged monthly on the average amount stored after compression. Capacity can be bought on demand or pre-paid.

Source
Cognite Data Fusion: How is it priced?

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

Snowflake: What Snowflake editions are there?

Snowflake sells four editions: Standard as the entry level offering, Enterprise for high growth and large scale customers, Business Critical for regulated industries handling sensitive data, and Virtual Private Snowflake for a completely isolated environment.

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.

Snowflake: Does Snowflake publish a per credit price?

Not on its pricing options page. Snowflake directs buyers to its Credit Consumption Table and a pricing calculator for the rates, which vary by edition, region and cloud provider.

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.

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