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Altair RapidMiner vs KNIME vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive Summary

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 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.7%, up from 6.5% compared to the previous year. The mindshare of KNIME is 11.7%, up from 9.8% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.7%, down from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Laurence Moseley - PeerSpot reviewer
Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms
When I started using RapidMiner, I found it difficult to get it to read the metadata. I wanted to use, for example, a pivot table, and it did not have the variable or the attribute names in it. There were no values. It took a long while to figure out how to do that, although it tends to do it automatically nowadays. RapidMiner is not utterly intuitive for beginners. Sometimes people have trouble distinguishing between a file in their own file system and a repository entry, and they cannot find their data. This is an area where this solution could be improved. It would be helpful to have some tutorials on communicating with Python. I found it a bit difficult at times to figure out which particular variable, or attribute, is going where in Python. It is probably a simple thing to do but I haven't mastered it yet. I'd like them to do a video on that. There are a large number of videos that are usually well-produced, but I don't think that they have one on that. Essentially, I would like to see how to communicate from RapidMiner to Python and from Python to RapidMiner. One of the things I do a lot of is looking at questionnaires where people have used Likert-type scales. I don't recommend Likert-type scales, but if they're properly produced, which is a lot of hard work and it's not usually done, they're really powerful and you can do things like normalizing holes on the Likert scale. That's not the same as normalizing your data in RapidMiner. So, I would want to get results with these Likert scales, pass it through RapidMiner, do a normalization and pass back both the raw scores and the normalized scores and put in some rules, which will say if it's high on the raw score and on the normalized score and low on the standard deviation, then you can trust it.
Laurence Moseley - PeerSpot reviewer
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,
reviewer1447110 - PeerSpot reviewer
Good technical support but too complex and not open-source
We're using Enterprise Guide simultaneously with Enterprise Miner. From my perspective, I believe that open-source analytics tools are closer to fitting our needs. We prefer open-source options like Anaconda. They offer good support and features. Anaconda also integrates well with Jupyter NET, which is important for us. Overall, on a scale from one to ten, I'd rate the solution at a five. If there were better protocols and wasn't as complex as it is, I'd rate it a bit higher.

Quotes from Members

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

Pros

"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."
"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."
"The data science, collaboration, and IDN are very, very strong."
"RapidMiner for Windows is an excellent graphical tool for data science."
"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."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"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 most valuable features are the Binary classification and Auto Model."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"From a user-friendliness perspective, it's a great tool."
"KNIME is very easy to handle and use. Anyone can use it, and it's easy to learn."
"We have found KNIME valuable when it comes to its visualization."
"The product is user-friendly."
"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."
"The solution is able to handle quite large amounts of data beautifully."
"The most valuable feature is the decision tree creation."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"Good data management and analytics."
"I like the way the product visually shows the data pipeline."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
 

Cons

"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"If they could include video tutorials, people would find that quite helpful."
"I would like to see more integration capabilities."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"The product must provide data-cleaning features."
"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."
"I would appreciate improvements in automation and customization options to further streamline processes."
"Improve the online data services."
"There should be better documentation and the steps should be easier."
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"From the point of view of the interface, they can do a little bit better."
"KNIME is not good at visualization."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"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."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"The solution is much more complex than other options."
"The initial setup is challenging if doing it for the first time."
"Technical support could be improved."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The product must provide better integration with cloud-native technologies."
"The visualization of the models is not very attractive, so the graphics should be improved."
"Virtualization could be much better."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
 

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."
"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."
"For the university, the cost of the solution is free for the students and teachers."
"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."
"KNIME assets are stand alone, as the solution is open source."
"It is free of cost. It is GNU licensed."
"I use the open-source version."
"KNIME offers a free version"
"KNIME is free and open source."
"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."
"This is an open-source solution that is free to use."
"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
"The solution must improve its licensing models."
"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."
"This solution is for large corporations because not everybody can afford it."
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Top Industries

By visitors reading reviews
University
11%
Computer Software Company
11%
Educational Organization
10%
Financial Services Firm
9%
Financial Services Firm
13%
Manufacturing Company
11%
Computer Software Company
9%
University
7%
Financial Services Firm
26%
University
12%
Educational Organization
9%
Manufacturing Company
8%
 

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. I...
What is your experience regarding pricing and costs for RapidMiner?
I'm not fully aware of RapidMiner's price because we had licenses provided, but from my analysis, it's moderately pri...
What needs improvement with RapidMiner?
Altair RapidMiner needs updates to its examples, particularly in business and marketing areas, and to the tool itself...
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?
For graphics, the interface is a little confusing. So, this is a point that could be improved.
What do you like most about SAS Enterprise Miner?
I like the way the product visually shows the data pipeline.
What is your experience regarding pricing and costs for SAS Enterprise Miner?
The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a...
What needs improvement with SAS Enterprise Miner?
The product must provide better integration with cloud-native technologies.
 

Also Known As

No data available
KNIME Analytics Platform
Enterprise Miner
 

Overview

 

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare
Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: March 2025.
844,944 professionals have used our research since 2012.