Altair RapidMiner vs Dataiku vs KNIME Business Hub comparison

Read 21 Dataiku reviews

5,913 Views
5,795 Comparison Views

100% willing to recommend

KNIME Business Hub

Read 62 KNIME Business Hub reviews

8,206 Views
5,908 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: March 2026).

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Data Science Platforms

March 2026

Helped 885,789 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 April 2026, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 4.2%, down from 7.8% compared to the previous year. The mindshare of Dataiku is 6.7%, down from 12.5% compared to the previous year. The mindshare of KNIME Business Hub is 6.8%, down from 11.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
KNIME Business Hub	6.8%
Dataiku	6.7%
Altair RapidMiner	4.2%
Other	82.3%

Data Science Platforms

Featured Reviews

Sachin Jagtap

Senior Manager, Digitalization of Supply Chain& Traceability at a non-profit with 501-1,000 employees

Gain insights and make predictions with intuitive tools and seamless data preparation

Altair RapidMiner is easy to use and intuitive with no coding required, making it a low code tool. It offers flexibility, allowing for extensive data preparation and initial insights, and facilitates building a chain of analysis. Additionally, it includes machine learning and AI tools to work on complex datasets. It is considered a stable product with a long-standing presence.

Read full review

Shubhamkumar Gomar

Senior Data Scientist at Deloitte

Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly

In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.

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NataliaRaffo

Co Founder & Chief Data Officer Cdo at NTT DATA

Workflow automation has accelerated advanced analytics and machine learning delivery

Sometimes it is a little bit difficult to use some nodes when we have many large-scale data, for example, CSV files with a large amount of data. It is sometimes difficult to try to import the data in KNIME Business Hub nodes because I think that some features that are in the CSV in text, for example, large text, is difficult for KNIME Business Hub to import these fields. I don't know why, but it is very difficult. We need to try to use different nodes for importing the data, such as File Reader and CSV Reader. However, I think that it is always the features that have much text, it is difficult for KNIME Business Hub to understand and import this information. I don't know why, or maybe I don't know if we don't know what the better option is to configure the node to import all the CSV or the data set. However, we have always had this problem. In some nodes, sometimes it is the same because sometimes, for example, I have a CSV and in my CSV, I have a feature that is, for example, a date. When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text, for example. We try to use their nodes that convert text to date, but sometimes it is difficult, and it is not immediate to transform the text into a date. So we needed to convert the text into a date in the CSV, and then import it again in the KNIME Business Hub node and try to have a good read of this field. I know that KNIME Business Hub has some nodes to convert text to date and others, but sometimes it is difficult to use these nodes. I don't know why. Maybe it needs a specific format for the date and we need to transform our feature in this option. So sometimes it is a large process to convert these features. However, sometimes we need to investigate and search for other nodes, and try with other nodes to import these cases.

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 can read a large number of file formats including CSV, Excel, and in particular, SPSS."

"It is easy to use and has a huge community that I can rely on for help. Moreover, it is interactive."

"The best part of RapidMiner is efficiency."

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

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

"This solution is a great tool for users that are experimenting and is an alternative to doing the coding and everything themselves."

"The best thing about RapidMiner is efficiency."

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

More Altair RapidMiner pros

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

"I like the interface, which is probably my favorite part of the solution; it is really user-friendly, colorful, and I think it is really beautiful and well-designed."

"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."

"Technical support is really, really good."

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

"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."

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

More Dataiku pros

"I believe the main benefits I receive from KNIME Business Hub are automation, because when I work through the workflow one time, I can reuse it later on, saving considerable time for many tasks."

"The solution is good for teaching, since there is no need to code."

"KNIME is more intuitive and easier to use, which is the principal advantage."

"Usability, and organising workflows in very neat manner. Controlling workflow through variables is something amazing."

"The data analytics capabilities in KNIME are excellent; it's not just a statistical ETL tool, as we can go deeper and do various types of tasks beyond straight analytics."

"Clear view of the data at every step of ETL process enables changing the flow as needed."

"The solution allows for sharing model designs and model operations with other data analysts."

"The product is open-source and therefore free to use."

More KNIME Business Hub pros

Cons

"Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning."

"Improve the online data services."

"RapidMiner isn't cheap. It's a complete solution, but it's costly."

"A great product but confusing in some way with regard to the user interface and integration with other tools."

"I would like to see wider adoption of the RapidMiner platform by the Open Source community as a viable alternative/companion to Python and R."

"Many things in the interface look nice, but they aren't of much use to the operator."

"RapidMiner loads very slowly, which is something that should be improved."

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

More Altair RapidMiner cons

"I think it would help if Data Science Studio added some more features and improved the data model."

"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."

"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."

"However, I feel that better documentation is necessary."

"I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete."

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."

"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."

More Dataiku cons

"Compared to the other data tools on the market, the user interface can be improved."

"The diversity of native algorithms could be improved."

"It could input more data acquisitions from other sources and it is difficult to combine with Python."

"KNIME is not scalable."

"I feel the query performance is slower than my old code."

"KNIME doesn't handle large datasets or a high number of records well."

"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."

"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."

More KNIME Business Hub 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 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."

"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."

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

"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."

"I use the tool's free version."

"KNIME Business Hub is expensive for small companies."

"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."

"KNIME offers a free version"

"This is a free open-source solution."

"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."

More KNIME Business Hub pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

11%

University

11%

Computer Software Company

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Energy/Utilities Company

Financial Services Firm

12%

Manufacturing Company

University

Educational Organization

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	6
Midsize Enterprise	2
Large Enterprise	13

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	16
Large Enterprise	31

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 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 vi...

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 whe...

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...

Databricks vs Altair RapidMiner

Comparisons

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Compared 4% of the time

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Compared 3% of the time

IBM SPSS Modeler vs Altair RapidMiner

Compared 3% of the time

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Databricks vs Dataiku

Compared 21% of the time

Alteryx vs Dataiku

Compared 10% of the time

Domino Data Science Platform vs Dataiku

Compared 5% of the time

Amazon SageMaker vs Dataiku

Compared 5% of the time

Microsoft Azure Machine Learning Studio vs Dataiku

Compared 3% of the time

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Alteryx vs KNIME Business Hub

Compared 8% of the time

Microsoft Azure Machine Learning Studio vs KNIME Business Hub

Compared 8% of the time

Databricks vs KNIME Business Hub

Compared 7% of the time

Microsoft Power BI vs KNIME Business Hub

Compared 6% of the time

Weka vs KNIME Business Hub

Compared 4% of the time

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Product Reports

Download Altair RapidMiner product report

Altair RapidMiner

April 2026

Download Dataiku product report

April 2026

Download KNIME Business Hub product report

KNIME Business Hub

March 2026

Also Known As

No data available

Dataiku DSS

KNIME Analytics Platform

Overview

Altair RapidMiner is a GUI-driven, code-free data science tool ideal for users seeking efficiency and user-friendliness, featuring automated data cleaning and versatile model support for diverse tasks.

Altair RapidMiner offers an accessible platform with drag-and-drop functionality, supporting multiple file formats to streamline data science workflows. It enables quick prototyping and integrates with APIs, Python, and R, enhancing user flexibility. Comprehensive documentation and tutorials support learning, while features like model fine-tuning and predictive analytics cater to advanced analysis. Enhancements in automation and deep learning, alongside improvements in data service integration and metadata handling, remain a focus for development.

What are the key features of Altair RapidMiner?

Code-Free Interface: Simplifies data science with GUI support.
Drag-and-Drop Functionality: Streamlines process setup.
Automated Data Cleaning: Saves time in data preparation.
Machine Learning Algorithms: Supports a wide range for various tasks.
API & Python/R Integration: Enhances flexibility for data projects.
Tutorials & Documentation: Provides robust learning resources.

What benefits and ROI can users expect?

Efficiency: Reduces time spent on data processing.
Flexibility: Offers adaptable integration options.
Scalability: Suited for both educational and business environments.
Usability: User-friendly interface encourages wider adoption.
Predictive Capabilities: Empowers advanced business analytics.

Industries such as telecom and finance utilize Altair RapidMiner for tasks like data preparation and forecasting. Universities employ it for education and research projects, while businesses apply it to areas such as financial crime management and market analysis. It assists companies in predicting customer behavior and analyzing pharmaceutical data, allowing seamless integration with other systems.

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