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Machine Learning · head to head

Dataiku vs Gumloop

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Gumloop logo

Gumloop

AI

AI infrastructure platform for building and deploying autonomous agents

From
Free
Rated
-

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.; Gumloop pro plan at $37/month may be limiting for enterprises considering spending caps
  • They diverge on capability: Dataiku covers Visual Flow, Gumloop covers No-code agent builder.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and Gumloop actually diverge.

Attributes where Dataiku and Gumloop differ
AttributeDataikuGumloop
Pricing modelfreemiumTiered subscription with usage credits
PlatformsLinux, Mac, Windows, WebWeb, Slack, Microsoft Teams, Gmail
CategoryMachine LearningAI
Founded2013Unknown

Identical on both: starting price (Free), free tier (Yes), 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 Dataiku

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

Only in Gumloop

  • No-code agent builder
  • 300+ app integrations
  • Company Brain
  • Self-improving agents
  • Multi-channel deployment
  • Role-based access
  • Budget controls
  • Audit logging

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 Gumloop
  • Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot Gumloop
  • Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot Gumloop
  • Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot Gumloop

Gumloop

  • CRM management and sales pipeline analysisnot Dataiku
  • Lead qualification and sales outreach automationnot Dataiku
  • Meeting preparation and call analysisnot Dataiku
  • Data analysis and automated reportingnot Dataiku
  • Content creation and knowledge base updatesnot 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.

Gumloop

  • Pro plan at $37/month may be limiting for enterprises considering spending caps
  • Requires enterprise plan for advanced security controls needed by large organizations
  • No permanent free tier beyond 14-day trial
  • Company Brain integration depends on having all tools connected

Pricing, plan by plan

Dataiku

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

Gumloop

Free
  • Free TrialFree
    • 14-day free trial of Pro plan
  • Enterprise$undefined/custom
    • Custom credit allocation
    • 35+ models plus custom proxy
    • Org-wide security controls

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.

Choose Gumloop if

  • You need no-code agent builder.
  • You want to start without paying.
  • You work on Web, Slack, Microsoft Teams, Gmail.
  • You also want 300+ app integrations.

Questions people ask

Is Dataiku or Gumloop better?
Neither clearly leads. Dataiku starts at Free and Gumloop at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Gumloop?
Dataiku starts at Free and Gumloop at Free.
Does Dataiku or Gumloop run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Gumloop runs on Web, Slack, Microsoft Teams, Gmail.
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 Gumloop is typically brought in for.
What can Dataiku do that Gumloop cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. Gumloop covers No-code agent builder, 300+ app integrations, Company Brain, Self-improving agents.

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.

Gumloop: Can non-technical users build agents with Gumloop?

Yes, Gumloop is designed for domain experts without programming skills. The no-code interface enables anyone who understands a task to automate it without coding.

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.

Gumloop: How many applications can Gumloop integrate with?

Gumloop integrates with 300+ business tools including Salesforce, HubSpot, Slack, Gmail, GitHub, Jira, and others. The Company Brain feature unifies data from all connected applications.

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.

Gumloop: What security features does Enterprise include?

Enterprise plans offer SCIM and SAML support, SOC 2 Type II compliance, custom MCP server hosting, advanced admin features, audit logging, and VPC deployments for data isolation.

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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