Altair RapidMiner vs Dataiku vs KNIME Business Hub comparison

Read 13 Dataiku reviews

5,844 Views
5,669 Comparison Views

100% willing to recommend

KNIME Business Hub

Read 60 KNIME Business Hub reviews

9,194 Views
6,436 Comparison Views

94% willing to recommend

Altair RapidMiner

KNIME Business Hub

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Altair RapidMiner, Dataiku, and KNIME Business Hub based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms.

To learn more, read our detailed Data Science Platforms Report (Updated: September 2025).

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Data Science Platforms

September 2025

Helped 869,832 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:

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.0%, down from 7.5% compared to the previous year. The mindshare of Dataiku is 11.7%, up from 10.9% compared to the previous year. The mindshare of KNIME Business Hub is 11.9%, up from 10.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
KNIME Business Hub	11.9%
Dataiku	11.7%
Altair RapidMiner	7.0%
Other	69.4%

Data Science Platforms

Featured Reviews

Rathnam Makam

Senior Technical Manager at a computer software company with 1,001-5,000 employees

A no-code tool that helps to build machine learning models

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. I haven't explored the tool's latest version, so I'm unaware of the current features. However, I think it would be beneficial if they could enhance capabilities related to deep neural networks, provide better support for generating UI, and allow for importing and utilizing large language models.

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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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Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

Has a drag-and-drop interface and AI capabilities

It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,

Read full review

Quotes from Members

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

Pros

"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."

"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."

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

"RapidMiner is very easy to use."

"RapidMiner for Windows is an excellent graphical tool for data science."

"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."

"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."

"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."

More Altair RapidMiner pros

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

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

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

"I believe the return on investment looks positive."

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

"Dataiku is highly regarded as it is a leader in the Gartner ranking."

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

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

More Dataiku pros

"It's a huge tool with machine learning features as well."

"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."

"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."

"The hardest part is keeping a tidy workspace because of the many nodes involved. When teaching, it would be helpful if there was more emphasis on how to group nodes effectively. For example, turning frequently used nodes into a single component can simplify things."

"This open-source product can compete with category leaders in ELT software."

"The product is user-friendly."

"I've tried to utilize KNIME to the fullest extent possible to replace Excel."

"It can handle an unlimited amount of data, which is the advantage of using Knime."

More KNIME Business Hub pros

Cons

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

"The price of this solution should be improved."

"It would be helpful to have some tutorials on communicating with Python."

"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."

"If they could include video tutorials, people would find that quite helpful."

"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."

"I think that they should make deep learning models easier."

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

More Altair RapidMiner cons

"In terms of enhancing collaboration within my team, I would not say Dataiku is the best one because it's so expensive."

"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."

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

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

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

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

More Dataiku cons

"To enhance accessibility and user-friendliness, there is a need for improvements in the interface and usability of deep learning and large-scale learning languages."

"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."

"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."

"The pricing needs improvement."

"KNIME is not scalable."

"The data visualization part is the area most in need of improvement."

"From the point of view of the interface, they can do a little bit better."

"We do not have much documentation in Portuguese."

More KNIME Business Hub cons

Pricing and Cost Advice

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

"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."

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

"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."

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

"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."

"KNIME is an open-source tool, so it's free to use."

"KNIME assets are stand alone, as the solution is open source."

"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."

"It is expensive to procure the license."

"We're using the free academic license just locally. I went for KNIME because they have a free academic license."

"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."

"With KNIME, you can use the desktop version free of charge as much as you like. I've yet to hit its limits. If I did, I'd have to go to the server version, and for that you have to pay. Fortunately, I don't have to at the moment."

"It's an open-source solution."

More KNIME Business Hub pricing and cost advice

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Top Industries

By visitors reading reviews

University

11%

Manufacturing Company

10%

Computer Software Company

10%

Educational Organization

10%

Financial Services Firm

17%

Manufacturing Company

10%

Computer Software Company

Energy/Utilities Company

Financial Services Firm

11%

University

Manufacturing Company

Computer Software 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	1
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	16
Large Enterprise	29

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. I...

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 l...

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...

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 mo...

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 compa...

What do you like most about KNIME?

Since KNIME is a no-code platform, it is easy to work with.

What is your experience regarding pricing and costs for KNIME?

I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.

What needs improvement with KNIME?

I have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer ver...

Tableau Enterprise vs Altair RapidMiner

Comparisons

Compared 8% of the time

Alteryx vs Altair RapidMiner

Compared 6% of the time

Microsoft Azure Machine Learning Studio vs Altair RapidMiner

Compared 4% of the time

IBM SPSS Modeler vs Altair RapidMiner

Compared 3% of the time

Databricks vs Altair RapidMiner

Compared 2% of the time

More Altair RapidMiner Competitors

Databricks vs Dataiku

Compared 24% of the time

Alteryx vs Dataiku

Compared 12% of the time

Amazon SageMaker vs Dataiku

Compared 9% of the time

Domino Data Science Platform vs Dataiku

Compared 5% of the time

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 4% of the time

More Dataiku Competitors

Microsoft Power BI vs KNIME Business Hub

Compared 10% of the time

Microsoft Azure Machine Learning Studio vs KNIME Business Hub

Compared 9% of the time

Alteryx vs KNIME Business Hub

Compared 8% of the time

Weka vs KNIME Business Hub

Compared 7% of the time

Databricks vs KNIME Business Hub

Compared 5% of the time

More KNIME Business Hub Competitors

Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

October 2025

Download Dataiku product report

October 2025

Download KNIME Business Hub product report

KNIME Business Hub

October 2025

Also Known As

No data available

Dataiku DSS

KNIME Analytics Platform

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.

KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.

KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.

What are the most important features of KNIME Business Hub?

No-Code Interface: Simplifies data preparation without coding expertise.
Node Library: Supports diverse data tasks, including ETL and machine learning.
Python and R Integration: Seamlessly connects with popular programming languages.
Automation Capabilities: Enhances workflow productivity.
Visual Workflow Tools: Offers efficient data handling with visual aids.

What benefits and ROI can users expect from KNIME Business Hub?

Increased Productivity: Streamlined data tasks reduce development time.
Community Support: Access to extensive resources and user assistance.
Cost-Effective: Robust performance even on standard hardware.
Accessible Learning Curve: Simplicity allows easy access for educational and professional use.
Enhanced Prototyping: Ideal for decision model testing.

KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.

Knime

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

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

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG