Dataiku Pricing Overview

Free Trial

Install Dataiku on Your Infrastructure

Free

3 Users

Download Free Edition on Mac, Linux, or virtual machine | Collaborate with up to 3 users | Prepare data and build basic data projects and apps (no deployment, automation, governance)

Try Dataiku Cloud for 14 Days

Free Trial

2 Users

Ready in under 2 minutes | Fully managed by Dataiku on our secure servers | Collaborate with up to 2 users | Start exploring end-to-end Dataiku features for building and automating AI projects

Use Dataiku Across Your Entire Organization

Paid Editions to scale AI with enterprise-wide collaboration, governance, ops, and model deployment features | Tailored offerings for any size team or business | Hosted by Dataiku or self-hosted

Dataiku offers three simple plans: (1) Free Edition, (2) Free Trial, and (3) Paid Editions.

Free Edition can be downloaded on your infrastructure now, and is designed for users to prepare data and build basic data projects and apps (no deployment, automation, nor governance).

Free Trial allows users to start exploring end-to-end Dataiku features for building and automating AI projects for 14 days in Dataiku Cloud.

Paid Editions allow any size team or business to scale AI with enterprise-wide collaboration, governance, ops, and model deployment features. Use Dataiku across your entire organization, hosted by Dataiku or self-hosted, with this tailored offering.

Dataiku has 3 pricing editions. Look at different pricing editions below and see what edition and features meet your budget and needs.

Pricing information for Dataiku is supplied by the software provider or retrieved from publicly accessible pricing materials. Final cost negotiations to purchase Dataiku must be conducted with the seller.

Pricing information was last updated on April 03, 2025

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Dataiku Pricing Reviews

(2)

Márcio B.

Engenheiro de dados sênior

Small-Business (50 or fewer emp.)

4/25/2025

"A Complete and Intuitive Platform for Data Science Projects"

5/5

What do you like best about Dataiku?

Dataiku stands out for its ease of use — the drag-and-drop interface combined with the option to code when necessary makes it accessible to a wide range of users. Implementation was smooth and well-supported by the customer success team. I use Dataiku frequently because it offers a vast number of features, from data preparation to model deployment. Integration with other tools like databases, cloud services, and APIs is straightforward, making the platform even more powerful for end-to-end projects. Review collected by and hosted on G2.com.

What do you dislike about Dataiku?

While overall the platform is excellent, some advanced settings and options could be a bit overwhelming for new users. Additionally, the pricing structure can be a limiting factor for smaller companies or teams. Review collected by and hosted on G2.com.

What problems is Dataiku solving and how is that benefiting you?

Dataiku is helping to solve the complexity of managing the full data science workflow, from data ingestion and preparation to model development and deployment. It centralizes collaboration between data scientists, analysts, and business users, ensuring that projects move faster and with better governance. The platform also reduces dependency on purely manual coding, making advanced analytics more accessible. This is benefiting me by significantly increasing productivity, improving project visibility, and enabling faster decision-making based on reliable, well-structured data pipelines. Review collected by and hosted on G2.com.

Logan S.

Data Scientist

Enterprise (> 1000 emp.)

4/24/2025

"Reduction of time to value"

3.5/5

What do you like best about Dataiku?

Visual layout makes data transformation more clear. Built in tools speed up development time in particular with tools like the LLM recipes and ML model "battle" Review collected by and hosted on G2.com.

What do you dislike about Dataiku?

I have noticed inconsistencies with how code is executed in a python notebook vs a python recipe. Sometimes that works in a recipe doesn't work in a notebook. Refusal to add global dark mode. Review collected by and hosted on G2.com.

Response from Taylor MECHAM of Dataiku

edit

We're glad to hear that you find the visual layout and built-in tools helpful for data transformation and improved development time. We appreciate your feedback about the inconsistencies with code execution between Python notebooks and recipes—we'll share this with our team for further review and improvement.