Altair RapidMiner vs Dataiku comparison

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Altair RapidMiner

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Executive SummaryUpdated on Dec 21, 2025

Altair RapidMiner and Dataiku compete in the data analytics and machine learning space. Customers often prefer Altair RapidMiner for its pricing structure and reliability, although Dataiku's extensive features can justify its higher cost.

Features: Altair RapidMiner offers an intuitive drag-and-drop interface, extensive data preparation capabilities, and effective machine learning tools, making it suitable for beginners. Dataiku provides a robust collaborative environment, advanced analytics support, and an efficient workflow management system, making it appealing for comprehensive project management.

Room for Improvement: Altair RapidMiner could enhance support for more advanced analytics features, improve scalability options, and offer more comprehensive API integration. Dataiku might work on reducing its complexity for new users, offer more competitive pricing options, and increase the flexibility of its deployment options.

Ease of Deployment and Customer Service: Altair RapidMiner is known for straightforward deployment and reliable support, ideal for quick implementation. Dataiku excels in detailed onboarding and resource availability, providing in-depth guidance and comprehensive documentation, beneficial for organizations with complex deployment needs.

Pricing and ROI: Altair RapidMiner is generally lower-cost with a solid return on investment due to quick setup. Dataiku requires a higher initial investment but can offer substantial long-term gains and scalability, rewarding those who fully leverage its advanced capabilities.

To learn more, read our detailed Altair RapidMiner vs. Dataiku Report (Updated: December 2025).

Altair RapidMiner vs. Dataiku

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Altair RapidMiner

Ranking in Data Science Platforms

8th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (4th)

Dataiku

Ranking in Data Science Platforms

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 4.4%, down from 7.7% compared to the previous year. The mindshare of Dataiku is 7.1%, down from 12.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Dataiku	7.1%
Altair RapidMiner	4.4%
Other	88.5%

Data Science Platforms

Featured Reviews

VictorSantos

Professor at Instituto Superior de Contabilidade e Administraçao de Coimbra

Utilize intuitive CRISP model support and predictive analytics features for effective data analysis

Altair RapidMiner is appreciated for its ease of use and the CRISP data mining model it supports, covering steps like data preparation, data understanding, and business understanding. The tool’s auto model feature is excellent as it allows simulation of models to select the best one. It is useful for predictive analytics with community support for model adjustments. I also find handling complex datasets promising, although there's a need for improvement with generative AI adaptation.

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PriyankaSharma3

Cdao/Global Head Of Data And Analytics at Givaudan Roure

Unified platform has accelerated model development and improved collaborative data science work

I think Dataiku could be improved or enhanced in future releases with more 'talk to my data' capabilities, maybe more NLP features, and maybe a platform to build agents. These improvements would benefit me and my processes because they will help us to continue using Dataiku as one platform; right now we are exploring other platforms for the features which are missing, and if they are available within the same platform, I think it will increase the usage of Dataiku further. I think the pricing and licensing of Dataiku is a bit expensive; it could be improved further, and I think they should have a different kind of licensing model as well.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Altair RapidMiner is appreciated for its ease of use and the CRISP data mining model it supports, covering steps like data preparation, data understanding, and business understanding."

"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."

"One of the most valuable features is the built-in data tuning feature. Once the model is built, we often struggle to increase its accuracy, but RapidMiner allows us to fine-tune variables. For Example, when working on a project, we can adjust the number of nodes or the depth of trees to see how accuracy changes. This flexibility lets us achieve higher accuracy compared to traditional automated machine-learning models"

"Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool."

"The most valuable feature is what the product sets out to do, which is extracting information and data."

"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."

"The most valuable features are the Binary classification and Auto Model."

"The documentation for this solution is very good, where each operator is explained with how to use it."

More Altair RapidMiner pros

"The best features Dataiku offers include the ability for users to use the node without having to code and the functionality related to low-code/no-code."

"I believe the return on investment looks positive."

"One of the valuable features of Dataiku is the workflow capability."

"Our clients can easily drag and drop components and use them on the spot."

"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"The most valuable feature is the set of visual data preparation tools."

More Dataiku pros

Cons

"One challenge I encountered while implementing RapidMiner was the lack of documentation. Since there aren't as many users, finding resources to learn the tool was initially difficult. To overcome this hurdle, I believe RapidMiner could improve by providing more tutorials tailored for new users."

"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."

"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."

"The price of this solution should be improved."

"Improve the online data services."

"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."

"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."

"About twenty-five percent of my problems involve image processing, and I found RapidMiner lacking in this domain. While we work on OCR and similar tasks, RapidMiner hasn't been as engaged in that field as other models. Some other models also support email processing, but RapidMiner doesn't offer this feature."

More Altair RapidMiner cons

"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."

"We still encounter some integration issues."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."

"There is room for improvement in terms of allowing for more code-based features."

"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."

"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."

"Dataiku's scalability is not one of the best solutions to scale."

More Dataiku cons

Pricing and Cost Advice

"The client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."

"For the university, the cost of the solution is free for the students and teachers."

"Although we don't pay licensing fees because it is being used within the university, my understanding is that the cost is between $5,000 and $10,000 USD per year."

"I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately priced, not too high or too low. It's worth the investment."

"I used an educational license for this solution, which is available free of charge."

"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."

"Pricing is pretty steep. Dataiku is also not that cheap."

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Top Industries

By visitors reading reviews

Manufacturing Company

12%

University

11%

Computer Software Company

10%

Financial Services Firm

17%

Computer Software Company

Manufacturing Company

Energy/Utilities Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

What do you like most about RapidMiner?

RapidMiner is a no-code machine learning tool. I can install it on my local machine and work with smaller datasets. It can also connect to databases, allowing me to build models directly on the dat...

What is your experience regarding pricing and costs for RapidMiner?

I started with a trial version. We are likely to purchase a license, which may offer additional features.

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

I am not the person involved in the process regarding pricing, setup cost, and licensing.

What needs improvement with Dataiku Data Science Studio?

To improve Dataiku, it could enhance its visualization features, as it is not possible in Dataiku to create direct visualizations or to integrate a web app directly or in a simpler way as it is pos...

What is your primary use case for Dataiku Data Science Studio?

My main use case for Dataiku is for data science and AI projects. I use Dataiku for a demand forecasting use case where the objective is to predict the demand for each product for the next four mon...

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Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

January 2026

Download Dataiku product report

January 2026

Also Known As

No data available

Dataiku DSS

Overview

Altair RapidMiner is a leading platform for data science and machine learning, offering a user-friendly interface with powerful tools for predictive analytics. It supports integration with APIs, Python, and cloud services for streamlined workflow creation.

RapidMiner provides an efficient data science environment featuring drag-and-drop functionality, automation tools, and a wide array of algorithms, making it adaptable for novices and experts alike. Users benefit from easy data preparation and analysis alongside robust support from a vibrant community. Challenges include better onboarding and deep learning model accessibility, alongside calls for enhanced image processing and large language model integration.

What features make Altair RapidMiner stand out?

Data science tools: Facilitates machine learning and predictive analytics.
Code-optional GUI: Enables non-programmers to create workflows seamlessly.
Integration: Supports APIs, Python, and cloud services.
Drag-and-drop functionality: Simplifies workflow creation for users.
Algorithm variety: Offers diverse methods for data analysis.

What benefits and ROI should users consider when evaluating?

Efficiency: Saves time in data preparation and workflow automation.
Accessibility: Intuitive design aids beginners and experts.
Community: Access to extensions and collaborative resources.
Documentation: Comprehensive tutorials enhance learning.

Altair RapidMiner is extensively used in business and academia, facilitating tasks like predictive analytics, segmentation, and deployment. In education, it supports data science teaching and research, while in industries such as telecom, banking, and healthcare, it's used for data mining, decision trees, and market analysis.

Altair

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto