Machine Learning · head to head
Dataiku vs Ollama
Dataiku
Machine Learning
Browser-based platform where visual data preparation and written code share one pipeline
- From
- Free
- Rated
- -
Ollama
Machine Learning
Open-source tool for running LLMs locally on desktop and servers
- 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.; Ollama requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Dataiku and Ollama actually diverge.
Identical on both: starting price (Free), pricing model (freemium), 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 Ollama
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 Ollama
- Regulated model risk environments needing documented lineage, sign-off and a record of how a production model was producednot Ollama
- Pushing heavy transformations down into a cloud warehouse while keeping the pipeline definition in one reviewable placenot Ollama
- Large enterprises replacing a sprawl of spreadsheets and unmanaged scripts with something a governance function will acceptnot Ollama
Ollama
- Local development and testing without API costs or rate limitsnot Dataiku
- Privacy-sensitive applications requiring data to remain on-devicenot Dataiku
- Cost-sensitive deployments where computational resources are already availablenot Dataiku
- Fully offline environments or air-gapped networksnot 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.
Ollama
- Requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines
- No hosted service option for inference; all computational burden falls to user
- Limited to open-weight models; cannot run proprietary models like GPT-4 or Claude locally
- Performance depends entirely on user's hardware; no SLAs or guarantees on speed
Pricing, plan by plan
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
Ollama
Free- FreeFree
- CLI, API, desktop apps
- Unlimited public models
- 40,000+ community integrations
- Pro$20/month
- Access to larger, more powerful cloud models
- Run 3 concurrent cloud models
- 50x more usage than Free
- Max$100/month
- Run 10 concurrent cloud models
- 5x more usage than Pro
- Team$25/month
- Per seat pricing (5-seat minimum = $125/month)
- Shared billing
- Zero data retention
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 Ollama if
- You want to start without paying.
- You work on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted).
Questions people ask
- Is Dataiku or Ollama better?
- Neither clearly leads. Dataiku starts at Free and Ollama at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dataiku or Ollama?
- Dataiku starts at Free and Ollama at Free.
- Does Dataiku or Ollama run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. Ollama runs on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted).
- 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 Ollama is typically brought in for.
- What can Dataiku do that Ollama 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.
Ollama: How much does Ollama cost?
Ollama is free to use with unlimited public models. Pro paid plans start at $20/month for 3 concurrent cloud models, or $100/month for Max with 10 concurrent models. Team plans cost $25/seat/month with a 5-seat minimum.
SourceDataiku: 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.
Ollama: What does the Ollama free tier include?
The free tier includes CLI and API access, unlimited public models, 40,000+ community integrations, and private data retention, though limited to 1 concurrent cloud model.
SourceDataiku: 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.
Ollama: How much usage is included with each Ollama plan?
Pro includes 50x more usage than Free, and Max includes 5x more usage than Pro. Session limits reset every 5 hours and weekly limits reset every 7 days across all tiers.
SourceDataiku: 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.
Ollama: Does Ollama log or train on user data?
No, Ollama explicitly states that prompt or response data is never logged or trained on, protecting user privacy across all plans.
SourceDataiku: 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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