Try our new research platform with insights from 80,000+ expert users

Altair RapidMiner vs H2O.ai comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Mar 4, 2025

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
23
Ranking in other categories
Predictive Analytics (3rd)
H2O.ai
Ranking in Data Science Platforms
20th
Average Rating
7.6
Reviews Sentiment
7.2
Number of Reviews
8
Ranking in other categories
Model Monitoring (6th)
 

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 H2O.ai is 1.5%, up from 1.5% 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.
Kashif Yaseen - PeerSpot reviewer
Plug-and-play convenience enhances productivity but needs better multimodal support
We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI The solution was plug-and-play, meaning most of the components were handled by the solution itself rather than building them from scratch. This was useful for our banking…

Quotes from Members

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

Pros

"The data science, collaboration, and IDN are very, very strong."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"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 very easy to use."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"The best part of RapidMiner is efficiency."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"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."
"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."
"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."
"The most valuable feature of H2O.ai is that it is plug-and-play."
"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"The ease of use in connecting to our cluster machines."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
 

Cons

"A great product but confusing in some way with regard to the user interface and integration with other tools."
"I would appreciate improvements in automation and customization options to further streamline processes."
"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."
"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."
"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 price of this solution should be improved."
"In the Mexican or Latin American market, it's kind of pricey."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"The model management features could be improved."
"The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability."
"I would like to see more features related to deployment."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
 

Pricing and Cost Advice

"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."
"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'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 client only has to pay the licensing costs. There are not any maintenance or hidden costs in addition to the license."
"We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
845,040 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
University
11%
Computer Software Company
11%
Educational Organization
10%
Financial Services Firm
9%
Financial Services Firm
21%
Computer Software Company
12%
Manufacturing Company
9%
Energy/Utilities Company
6%
 

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'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.
What needs improvement with RapidMiner?
Altair RapidMiner needs updates to its examples, particularly in business and marketing areas, and to the tool itself. The user interface should be improved. Incorporating generative AI as an AI as...
What needs improvement with H2O.ai?
H2O.ai can improve in areas like multimodal support and prompt engineering. They are already working on updates and changes. Although I haven't explored all the new products they've added to their ...
What is your primary use case for H2O.ai?
We mostly used the solution in the domain that I'm working. We had most of the use cases around chatbots and conversational BI.
What advice do you have for others considering H2O.ai?
It is important to address data privacy concerns and ensure you're choosing the right vendor that meets your use case demands. Also, you may leave my name, Kashif, but please keep the company name ...
 

Comparisons

 

Overview

 

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Find out what your peers are saying about Altair RapidMiner vs. H2O.ai and other solutions. Updated: March 2025.
845,040 professionals have used our research since 2012.