Altair RapidMiner vs H2O.ai comparison

Altair and H2O.ai are both solutions in the Data Science Platforms category. Altair is ranked #7 with an average rating of 8.1, while H2O.ai is ranked #20 with an average rating of 7.0. Altair holds a 7.8% mindshare in Data Science Platforms, compared to H2O.ai’s 1.7% mindshare. Additionally, 96% of Altair users are willing to recommend the solution, compared to 100% of H2O.ai users who would recommend it.

Altair RapidMiner

Read 24 Altair RapidMiner reviews

4,773 Views
745 Comparison Views

96% willing to recommend

H2O.ai

Read 8 H2O.ai reviews

1,152 Views
379 Comparison Views

100% willing to recommend

Altair RapidMiner

H2O.ai

Comparison Buyer's Guide

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Executive SummaryUpdated on Jun 8, 2025

Altair RapidMiner and H2O.ai are competing in the data analytics and machine learning sector. H2O.ai has the upper hand due to its advanced machine learning capabilities and innovative features, providing superior value despite higher costs.

Features: Altair RapidMiner offers a user-friendly interface with extensive data preparation tools, effective visualization, and automation capabilities. It facilitates a no-code approach, making it accessible for non-programmers. H2O.ai stands out with its advanced machine learning algorithms and integration with popular data science languages. It provides flexible deployment options and deep integration with APIs and cloud computing environments.

Room for Improvement: Altair RapidMiner could enhance its generative AI adaptation and extend its current feature set to better handle complex datasets. H2O.ai might improve its deployment complexity and provide more intuitive onboarding processes. Both products could benefit from broader algorithmic explanations to avoid bias in model selection and deployment.

Ease of Deployment and Customer Service: Altair RapidMiner is known for its straightforward deployment process and responsive customer support. H2O.ai, while offering more complex deployment, provides a wealth of scalability options and technical expertise within its support services, ensuring robust assistance for complex technical issues.

Pricing and ROI: Altair RapidMiner is perceived to have a balanced pricing structure with good initial ROI. Although H2O.ai is more costly upfront, its advanced analytics capabilities justify the expense, often leading to higher ROI in intricate use cases.

To learn more, read our detailed Altair RapidMiner vs. H2O.ai Report (Updated: June 2025).

Buyer's Guide

Altair RapidMiner vs. H2O.ai

June 2025

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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

Ranking in other categories

Predictive Analytics (2nd)

H2O.ai

Ranking in Data Science Platforms

20th

Average Rating

7.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Model Monitoring (5th)

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Altair RapidMiner is 7.8%, up from 7.0% compared to the previous year. The mindshare of H2O.ai is 1.7%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Gopi Manoj Vuyyuru

Technical Support Team Lead at HCLTech

An open-source software tool for data and text mining with an excellent built-in data tuning feature for achieving better accuracy

I would advise new users to remember that RapidMiner requires building your pipeline. You need to start from scratch, which includes loading the data, cleaning it, making visualizations, and training the model and is not fully automated. I wouldn't thoroughly recommend it if you don't have working knowledge. There are some support articles and built-in hints, but platforms like DataRobot, which are fully automated, might be better for you if you're starting. Learning RapidMiner as a beginner is straightforward. You need to understand how a model works, know the different stages involved in modelling, and the importance of cleaning data. RapidMiner has a learning platform where you can learn the basic modules and how things work. They also offer certifications if you complete courses and exams. It's a good option for beginners to thoroughly learn about different models and the modelling stages. Overall, I would rate it an eight out of ten.

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Kashif Yaseen

Trainee Decision Scientist at a tech services company with 1,001-5,000 employees

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…

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Quotes from Members

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

Pros

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

"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."

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

"The solution is stable."

"RapidMiner is very easy to use."

"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

"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."

"The most valuable feature of H2O.ai is that it is plug-and-play."

"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."

"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."

"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."

"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."

Cons

"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."

"The price of this solution should be improved."

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

"Improve the online data services."

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

"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."

More Altair RapidMiner cons

"I would like to see more features related to deployment."

"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."

"The model management features could be improved."

"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."

"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."

"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

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."

"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."

"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."

"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."

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Top Industries

By visitors reading reviews

University

11%

Computer Software Company

11%

Educational Organization

Financial Services Firm

19%

Computer Software Company

13%

Manufacturing Company

10%

Educational Organization

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...

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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.

See all answers

What needs improvement with RapidMiner?

Currently, I am unsure of all the AI features available in Altair RapidMiner, particularly advanced AI capabilities like neural networks and deep learning. It would be beneficial if the platform co...

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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 ...

See all answers

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.

See all answers

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 ...

See all answers

Comparisons

KNIME vs Altair RapidMiner

Compared 51% of the time

Dataiku vs Altair RapidMiner

Compared 16% of the time

Tableau vs Altair RapidMiner

Compared 7% of the time

Alteryx vs Altair RapidMiner

Compared 7% of the time

Altair Knowledge Studio vs Altair RapidMiner

Compared 1% of the time

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Compared 25% of the time

Amazon SageMaker vs H2O.ai

Compared 21% of the time

Databricks vs H2O.ai

Compared 20% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 17% of the time

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Product Reports

Buyer's Guide

Altair RapidMiner

June 2025

Download Altair RapidMiner product report

Buyer's Guide

Data Science Platforms

June 2025

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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

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.

H2O.ai

Sample Customers

PayPal, Deloitte, eBay, Cisco, Miele, Volkswagen

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco

Buyer's Guide

Altair RapidMiner vs. H2O.ai

June 2025

Free Report: Altair RapidMiner vs. H2O.ai

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