Altair RapidMiner vs Dataiku comparison

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Altair RapidMiner

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Executive SummaryUpdated on Jun 8, 2025

Altair RapidMiner and Dataiku are competing in the data analytics and machine learning platforms category. Although Dataiku seems to have a superior feature set, Altair RapidMiner stands out with its pricing and support effectiveness, which may appeal to organizations with budget constraints.

Features: Altair RapidMiner offers drag-and-drop modeling, integration with multiple data sources, and a user-friendly interface, making it accessible for beginners. Dataiku provides collaborative features, a wide range of prebuilt connectors, and automation tools that streamline the analytics process and offer advanced functionality for experienced users.

Room for Improvement: Altair RapidMiner could enhance its adaptability to cutting-edge AI developments and offer more seamless integration with other modern tools. Dataiku might improve its pricing structure and simplify its comprehensive deployment requirements to better cater to smaller businesses or startups.

Ease of Deployment and Customer Service: Altair RapidMiner supports a simpler deployment process and extensive customer service options, easing setup and providing a responsive support experience. Dataiku's deployment model is robust, but it is more detailed and may require additional time, which larger enterprises typically manage well.

Pricing and ROI: Altair RapidMiner is known for its budget-friendly pricing, often leading to a quicker ROI, fitting well with organizations prioritizing cost-efficiency. Dataiku, with a higher setup cost, justifies the expenditure through its comprehensive feature offerings, delivering significant long-term benefits for enterprises seeking extensive functionality.

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

Altair RapidMiner vs. Dataiku

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Helped 856,873 peers since 2012

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

7th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Predictive Analytics (2nd)

Dataiku

Ranking in Data Science Platforms

6th

Average Rating

8.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.8%, up from 7.0% compared to the previous year. The mindshare of Dataiku is 13.0%, up from 8.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Gopi Manoj Vuyyuru

Technical Support Team Lead at HCLTech

An open-source software tool for data and text mining with an excellent built-in data tuning feature for achieving better accuracy

I would advise new users to remember that RapidMiner requires building your pipeline. You need to start from scratch, which includes loading the data, cleaning it, making visualizations, and training the model and is not fully automated. I wouldn't thoroughly recommend it if you don't have working knowledge. There are some support articles and built-in hints, but platforms like DataRobot, which are fully automated, might be better for you if you're starting. Learning RapidMiner as a beginner is straightforward. You need to understand how a model works, know the different stages involved in modelling, and the importance of cleaning data. RapidMiner has a learning platform where you can learn the basic modules and how things work. They also offer certifications if you complete courses and exams. It's a good option for beginners to thoroughly learn about different models and the modelling stages. Overall, I would rate it an eight out of ten.

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RichardXu

Data Science Lead at a mining and metals company with 10,001+ employees

The platform organizes workflows visually and efficiently

One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.

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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

"RapidMiner is very easy to use."

"I like not having to write all solutions from code. Being able to drag and drop controls, enables me to focus on building the best model, without needing to search for syntax errors or extra libraries."

"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 data stored there. RapidMiner offers a wider range of operators than other tools like Dataiku, making it a better option for my needs."

"The best part of RapidMiner is efficiency."

"The solution is very intuitive and powerful."

"The solution is stable."

"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."

"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."

More Altair RapidMiner pros

"I rate the overall product as eight out of ten."

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

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

"Cloud-based process run helps in not keeping the systems on while processes are running."

"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."

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

"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."

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

More Dataiku pros

Cons

"I would like to see more integration capabilities."

"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."

"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 product must provide data-cleaning features."

"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."

"I would like to see all users have access to all of the deep learning models, and that they can be used easily."

"Improve the online data services."

"RapidMiner can improve deep learning by enhancing the features."

More Altair RapidMiner cons

"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."

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

"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."

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

"The ability to have charts right from the explorer would be an improvement."

"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."

"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."

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

More Dataiku cons

Pricing and Cost Advice

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

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

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

"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."

"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."

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

"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."

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Educational Organization

Financial Services Firm

18%

Computer Software Company

Manufacturing Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.

What needs improvement with Dataiku Data Science Studio?

There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend ...

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

My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are uti...

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Product Reports

Altair RapidMiner

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Also Known As

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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

Altair RapidMiner vs. Dataiku