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Machine Learning · head to head

Dataiku vs Sourcegraph Cody

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
Sourcegraph Cody logo

Sourcegraph Cody

AI

Enterprise AI coding assistant with whole-codebase context

From
$59/month
Rated
-
Full reviewWebsite

The short version

  • Only Dataiku has a free tier, so it costs nothing to try first.
  • 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.; Sourcegraph Cody no longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • They diverge on capability: Dataiku covers Visual Flow, Sourcegraph Cody covers Multi-repository context.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and Sourcegraph Cody actually diverge.

Attributes where Dataiku and Sourcegraph Cody differ
AttributeDataikuSourcegraph Cody
Starting priceFree$59/month
Pricing modelfreemiumquote
Free tierYesNo
PlatformsLinux, Mac, Windows, Webweb, windows, mac, linux
CategoryMachine LearningAI

Identical on both: user rating (Not yet rated), founded (2013).

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 Sourcegraph Cody

  • Multi-repository context
  • Large context window
  • Context filters
  • Model flexibility
  • IDE integration

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

Sourcegraph Cody

  • Cross-repository code understanding for large engineering orgsnot Dataiku
  • AI-assisted code review and refactoring at enterprise scalenot Dataiku
  • Enforcing data-boundary controls when using third-party LLMsnot Dataiku
  • Codebase-aware chat and autocomplete for developersnot 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.

Sourcegraph Cody

  • No longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • Priced substantially higher than many competing AI coding assistants, with Enterprise plans typically requiring annual contracts
  • Sourcegraph has shifted its individual-developer focus to a separate product, Amp, creating uncertainty about Cody's long-term product priority
  • Requires integration with Sourcegraph's broader code intelligence platform rather than working as a lightweight standalone extension

Pricing, plan by plan

Dataiku

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

Sourcegraph Cody

$59/month
  • Enterprise$59/month
    • Whole-codebase AI context
    • Context filters for sensitive code
    • Multi-repository analysis

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 Sourcegraph Cody if

  • You need multi-repository context.
  • You work on web, windows, mac, linux.
  • You also want large context window.
Sourcegraph Cody review

Questions people ask

Is Dataiku or Sourcegraph Cody better?
Neither clearly leads. Dataiku starts at Free and Sourcegraph Cody at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Sourcegraph Cody?
Dataiku has a free tier; the other does not. Paid plans start at Free for Dataiku and $59/month for Sourcegraph Cody.
Does Dataiku or Sourcegraph Cody run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Sourcegraph Cody runs on web, windows, mac, linux.
Can I use Dataiku for free?
Yes. Dataiku has a free tier, so you can try it without paying. Sourcegraph Cody starts at $59/month.
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 Sourcegraph Cody is typically brought in for.
What can Dataiku do that Sourcegraph Cody cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. Sourcegraph Cody covers Multi-repository context, Large context window, Context filters, Model flexibility.

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.

Sourcegraph Cody: Is Sourcegraph Cody still available to individual developers?

No, as of mid-2025 Cody Free and Pro plans were discontinued; Cody is now sold only as part of Sourcegraph's Enterprise plan, which requires an annual contract.

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.

Sourcegraph Cody: How much does Sourcegraph Enterprise cost?

Enterprise plans start around $16,000 and scale with team size and seat count, including bundled AI credits; exact pricing requires a sales quote.

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.

Sourcegraph Cody: How does the AI credit system work on Enterprise plans?

Each plan includes a pooled allocation of AI credits shared across the organization; credits do not expire and roll over at renewal, with volume credit add-ons available.

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.

Sourcegraph Cody: What happens if my organization exceeds its credit allocation?

Sourcegraph's pricing page addresses overage and offers additional volume credit buckets for teams that need more than their committed allocation.

Source
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.

Sourcegraph Cody: Is a free trial available for Sourcegraph Enterprise?

Sourcegraph's pricing page lists free trial availability as one of its published FAQ topics for prospective Enterprise customers.

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