Softwr

Machine Learning · head to head

Dataiku vs Snowflake

Dataiku logo

Dataiku

Machine Learning

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

From
Free
Rated
-
Full reviewWebsite
Snowflake logo

Snowflake

Machine Learning

The AI Data Cloud for enterprise data warehousing

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.; 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: Dataiku covers Visual Flow, Snowflake covers Separated Compute/Storage.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dataiku and Snowflake actually diverge.

Attributes where Dataiku and Snowflake differ
AttributeDataikuSnowflake
Pricing modelfreemiumUnknown
PlatformsLinux, Mac, Windows, WebWeb, API
Founded20132012

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 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.

Dataiku

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

Snowflake

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

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

Dataiku

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

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 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 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 Dataiku or Snowflake better?
Neither clearly leads. Dataiku starts at Free and Snowflake at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dataiku or Snowflake?
Dataiku starts at Free and Snowflake at Free.
Does Dataiku or Snowflake run on more platforms?
Dataiku runs on Linux, Mac, Windows, Web. Snowflake runs on Web, API.
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 Snowflake is typically brought in for.
What can Dataiku do that Snowflake cannot?
Dataiku covers Visual Flow, Visual recipes, Code recipes and notebooks, Computation pushdown. Snowflake covers Separated Compute/Storage, Near-zero Maintenance, Data Sharing, Time Travel.

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.

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
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.

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
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.

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
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.

Share

Related pages

More on Dataiku

More on Snowflake

Keep looking

Other head to heads