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Machine Learning · head to head

Dataiku vs OpenRouter

Dataiku logo

Dataiku

Machine Learning

Browser-based platform where visual data preparation and written code share one pipeline

From
Free
Rated
-
Full reviewWebsite
OpenRouter logo

OpenRouter

Machine Learning

Unified API gateway routing requests across 500+ models from 80+ providers

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dataiku visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.; OpenRouter no free tier; all usage incurs cost
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and OpenRouter actually diverge.

Attributes where Dataiku and OpenRouter differ
AttributeDataikuOpenRouter
Pricing modelfreemiumusage-based
PlatformsLinux, Mac, Windows, WebAPI, Web
Founded2013Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

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 Dataiku

  • Visual Flow
  • Visual recipes
  • Code recipes and notebooks
  • Computation pushdown
  • Automated machine learning
  • Scenarios
  • Node topology
  • Governance features

Only in OpenRouter

Nothing recorded that Dataiku does not also cover.

What people use each for

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

Dataiku

  • Organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extractsnot OpenRouter
  • Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot OpenRouter
  • Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot OpenRouter
  • Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot OpenRouter

OpenRouter

  • Multi-model applications optimising for cost or performancenot Dataiku
  • Provider-agnostic deployments avoiding vendor lock-innot Dataiku
  • Enterprise applications with custom data policies and provider requirementsnot Dataiku
  • Development workflows testing multiple models without code changesnot Dataiku

Where each one falls short

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

Dataiku

  • Visual recipes are stored as Dataiku's own configuration and do not export as runnable SQL or Python, so a Flow with hundreds of visual steps has to be rebuilt from scratch if the organisation ever leaves, and that cost rises with every project added.
  • Production requires separate automation and API nodes, each installed and licensed, so the figure quoted for building models is not the figure for running them.
  • Licensing is per user across tiers, and the lower tiers are constrained enough that occasional contributors frequently end up needing a full seat, which makes a wide rollout cost more than the initial estimate suggested.
  • A self-hosted installation needs a dedicated administrator for upgrades, connection management, permissions and node topology, so the licence is a fraction of the real cost of ownership.
  • Computation pushes down to the warehouse or Spark cluster where it is billed by that provider, so a platform sold on making analysts self-sufficient can generate a large warehouse bill that nobody attributes back to it.

OpenRouter

  • No free tier; all usage incurs cost
  • Pricing varies by model; specific rates not published on main site without account access
  • Adds latency through additional routing layer compared to direct provider APIs
  • Dependent on upstream provider uptime and API compatibility

Pricing, plan by plan

Dataiku

Free
  • Free EditionFree
    • Single user
    • Core features
  • EnterpriseFree
    • Full platform
    • Collaboration
    • MLOps

OpenRouter

Free
  • FreeFree
    • 50 requests per day
    • Access to 25+ free models across 4 providers
    • Community support
  • Pay-as-you-go$null/variable
    • 5.5% platform fee on inference costs
    • Access to 500+ models across 80+ providers
    • Email support
  • Enterprise$null/custom
    • Negotiable platform fees
    • 200,000 USD of list price inference per month with no fees, then 5% fee after
    • SSO/SAML support

Which should you pick?

Choose Dataiku if

  • You need visual flow.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want visual recipes.
Dataiku review

Choose OpenRouter if

  • You want to start without paying.
  • You work on API, Web.
OpenRouter review

Questions people ask

Is Dataiku or OpenRouter better?
Neither clearly leads. Dataiku starts at Free and OpenRouter at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or OpenRouter?
Dataiku starts at Free and OpenRouter at Free.
Does Dataiku or OpenRouter run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. OpenRouter runs on API, Web.
Can I use Dataiku for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dataiku best used for?
Dataiku is most often used for organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts, regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced, pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable place, large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will accept. Of those, organisations where analysts and data scientists must collaborate on the same pipeline rather than exchanging extracts and regulated model risk environments needing documented lineage, sign-off and a record of how a production model was produced are not what OpenRouter is typically brought in for.
What can Dataiku do that OpenRouter cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown.

Answered from the vendors’ own pages

Dataiku: Is there a free version?

There is a free edition with limits on users and features, adequate for evaluation and personal work. Anything a team runs in production is a negotiated commercial agreement.

OpenRouter: How much does OpenRouter charge?

OpenRouter charges a 5.5% platform fee on top of the actual inference costs from selected models. Customers purchase credits on a pay-as-you-go basis with no subscriptions or minimum spend requirements.

Source
Dataiku: Do I have to write code to use it?

No. That is the premise. An analyst can build a complete pipeline through visual recipes, and a data scientist can write Python next to it in the same Flow.

OpenRouter: Is there a free tier?

Yes. OpenRouter offers a free tier with 50 requests per day and access to 25+ free models across 4 providers. The free tier provides community support only.

Source
Dataiku: Where does the computation actually run?

Wherever you connect it. Transformations are pushed down into the warehouse, database or Spark cluster where the data lives, which is efficient and also means the compute cost appears on that provider's bill rather than Dataiku's.

OpenRouter: What does the Enterprise plan include?

The Enterprise plan includes 200,000 USD of list price inference per month at no cost, with a 5% platform fee applied to usage above that threshold. It also includes SSO/SAML support, contractual SLAs, and dedicated support with a shared Slack channel.

Source
Dataiku: Can I export my work if we leave?

Code recipes are your code and leave with you. Visual recipes do not export as equivalent code, so the visual portion of a Flow has to be reimplemented, and that portion tends to be the majority in the projects where the platform succeeded best.

Dataiku: Self-hosted or cloud?

Both are offered. Self-hosting gives control over data residency and networking and requires an administrator; the managed cloud removes that work and moves the constraint to what the vendor's environment supports.

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