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

"Using the GUI, I can have models and algorithms drag and drop nodes."

"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."

"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."

"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."

"I've been using a lot of components from the Strategic Extension and Python Extension."

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

"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"

More Altair RapidMiner pros

"Data Science Studio's data science model is very useful."

"The solution is quite stable."

"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."

"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."

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

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

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

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

More Dataiku pros

"This solution is easy to use and it can be used to create any kind of model."

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

"It has allowed us to easily implement advanced analytics into various processes."

"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."

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

"We have been able to appreciate the considerable reduction in prototyping time."

"Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis."

"I've never had any problems with stability."

More KNIME Business Hub pros

Cons

"In the Mexican or Latin American market, it's kind of pricey."

"Altair RapidMiner needs updates to its examples, particularly in business and marketing areas, and to the tool itself. The user interface should be improved."

"The price of this solution should be improved."

"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 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."

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

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

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

More Altair RapidMiner cons

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

"We still encounter some integration issues."

"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."

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

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

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

"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 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."

More Dataiku cons

"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."

"In the last update, KNIME started hiding a lot of the nodes. It doesn't mean hiding, but you need to know what you're looking for. Before that, you had just a tree that you could click, and you could get an overview of what kind of nodes do I have. Right now, it's like you need to know which node you need, and then you can start typing, but it's actually more difficult to find them."

"I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial."

"The pricing needs improvement."

"The graphic features of KNIME need improvement"

"It could be easier to use."

"Occasionally, when using the GET object, there might be issues due to the velocity of the lines or the IT system of the commission."

"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."

More KNIME Business Hub cons

Pricing and Cost Advice

"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."

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

"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."

"They have different versions, but I am using the open-source one."

"KNIME is a cheap product. I currently use KNIME's open-source version."

"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."

"It's an open-source solution."

"It is expensive to procure the 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."

"I use the open-source version."

"There is a Community Edition and paid versions available."

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

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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