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Dataiku
Browser-based platform where visual data preparation and written code share one pipeline
As of 30 August 2026, Dataiku is free to use. Dataiku puts analysts and data scientists in the same project, with point-and-click recipes and Python or SQL recipes producing the same kind of dataset. Softwr lists it under Machine Learning. Dataiku is launched in 2013, available on Linux, macOS, Windows, Web.
Overview
What Dataiku does
Dataiku is a data science and analytics platform from the French company of the same name, used through a browser and installed either on your own infrastructure or consumed as Dataiku Cloud. Work is organised into projects, each containing a Flow: a visual graph of datasets connected by recipes, where a recipe is either a configured transformation or code in Python, R or SQL, and both kinds sit in the same pipeline. Around that it adds notebooks, automated machine learning, dashboards, scenarios for scheduling, a model registry and governance features. Production uses separate nodes, a design node for building, an automation node for scheduled work and API nodes for real-time scoring, each of which is installed and licensed. The distinguishing property is that it is the only serious attempt at a single artefact an analyst and a data scientist can both edit. A visual recipe built by someone in finance and a Python recipe written by an engineer produce the same kind of dataset in the same Flow, and computation pushes down to Snowflake, BigQuery, a database or Spark rather than pulling data into the tool. That is what justifies the price: it is bought to delete the handoff between the person who knows what a number means and the person who can compute it. The buyers are large enterprises on negotiated annual contracts priced by user tier and by node, typically a substantial six-figure commitment, and a self-hosted installation needs an administrator whose job it becomes. The trade-off is the Flow itself. Visual recipes do not export as runnable SQL or Python, so a project built over two years cannot be lifted to another platform without being rebuilt, and the more successfully analysts adopt the visual half, the less portable the organisation's work becomes. That is not an accident of the design, it is the design.
What people use it 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
Related searches
The honest half
Where it falls short
Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about 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.
Cross-shopped
What people choose instead of Dataiku
Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.
- DataikuvsGoogle Vertex AI
Google Vertex AI: Unified ML platform to build, deploy, and scale AI models
- DataikuvsAzure Machine Learning
Azure Machine Learning: Enterprise-grade machine learning service
- DataikuvsDataRobot
DataRobot: Enterprise AI platform for automated machine learning
Pricing
What Dataiku costs
Taken from the vendor's own pricing page. Prices move, so check before you buy.
Free Edition
Free
- Single user
- Core features
Enterprise
Free
- Full platform
- Collaboration
- MLOps
Capabilities
Features
Visual Flow
A project-level graph of datasets and recipes showing how every output was produced
Visual recipes
Joins, aggregations, filters, pivots and cleaning configured through forms rather than code
Code recipes and notebooks
Python, R and SQL steps in the same pipeline as visual ones, with notebooks for exploration
Computation pushdown
Executes transformations in Snowflake, BigQuery, a database or Spark instead of moving data into the platform
Automated machine learning
Trains and compares model families with cross validation and produces interpretability reports
Scenarios
Scheduling and triggering of pipeline runs with conditions, checks and notifications
Node topology
Separate design, automation and API nodes so building, scheduled production and real-time scoring are isolated
Governance features
Model registry, sign-off workflows and documentation aimed at regulated model risk processes
Connections and plugins
Managed connectors to warehouses, object storage and applications, extensible with custom plugins
Answered, with sources
Questions people ask
Each answer names the page it came from, so you can check it rather than take our word for it.
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.
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.
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.
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.
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.
Behind it
Who makes Dataiku
- Company
- Dataiku
- Based in
- New York, New York
Keep looking
Where to go from Dataiku
- Dataiku alternativesEvery product people weigh against it
- Dataiku pricingPlans, floors and what the tiers exclude
- Dataiku badgesWhich rules it meets, and the figure behind each
- All Machine Learning softwareThe full category
- Best Machine Learning softwareThe shortlist, and how it was cut
Best Machine Learning software for
Compare Dataiku with
- Azure Machine Learning
- DataRobot
- AWS SageMaker
- Anaconda
- Google Vertex AI
- RapidMiner
- Domino Data Lab
- KNIME
- Weights & Biases
- Neptune.ai
- ClearML
- Python
- Groq
- Haystack
- IBM SPSS
- JMP
- Minitab
- Mistral AI
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Softwr does not host reviews and shows no star rating for Dataiku, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.
More on Dataiku
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Every tier, and where the cost actually lands
Compare Dataiku
Put it head to head with anything we hold
Dataiku badge
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