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H2O.ai vs Microsoft Azure Machine Learning Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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

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)
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
4th
Average Rating
7.6
Reviews Sentiment
7.0
Number of Reviews
61
Ranking in other categories
AI Development Platforms (3rd)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of H2O.ai is 1.5%, up from 1.5% compared to the previous year. The mindshare of Microsoft Azure Machine Learning Studio is 5.3%, down from 9.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

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…
Takayuki Umehara - PeerSpot reviewer
Streamlined workflows with drag and drop convenience but needs enhancements in AI
I use Machine Learning Studio for system reselling and integration Machine Learning Studio is easy to use, with a significant feature being the drag and drop interface that enhances workflow without any complaints. It provides a return on investment and cost savings, proving beneficial for…

Quotes from Members

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

Pros

"The ease of use in connecting to our cluster machines."
"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."
"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."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"The most valuable feature of H2O.ai is that it is plug-and-play."
"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."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"Their support is helpful."
"​It has helped in reducing the time involved for coding using R and/or Python."
"Machine Learning Studio is easy to use."
"One of the notable advantages is that it offers both a visual designer, which is user-friendly, and an advanced coding option."
"The initial setup is very simple and straightforward."
"It's easy to use."
"Regarding the technical support for the solution, I find the documentation provided comprehensive and helpful."
"It helps in building customized models, which are easy for clients to use​.​​"
 

Cons

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"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."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"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."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"I would like to see more features related to deployment."
"Overall, the icons in the solution could be improved to provide better guidance to users. Additionally, the setup process for the solution could be made easier."
"Operability with R could be improved."
"The speed of deployment should be faster, as should testing."
"The pricing policy should be improved. I find the pricing to be not a good story in this case, as it is not affordable for everyone."
"They should have a desktop version to work on the platform."
"A problem that I encountered was that I had to pay for the model that I wanted to deploy and use on Azure Machine Learning, but there wasn't any option that that model can be used in the designer."
"The high price of the product is an area of concern where improvements are required."
"Stability-wise, you may face certain problems when you fail to refresh the data in the solution."
 

Pricing and Cost Advice

"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."
"When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly."
"We pay only the Azure costs for what we use, which involves some subscription costs. But essentially, you pay for what you use. There are no extra costs in addition to the standard licensing fees."
"The solution operates on a pay-per-use model."
"I used the free student license for a few months to operate the solution, but I'll have to pay for it if I want to do more now."
"From a developer's perspective, I find the price of this solution high."
"ML Studio's pricing becomes a numbers game."
"The solution cost is high."
"The platform's price is low."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
12%
Manufacturing Company
8%
Educational Organization
6%
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

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 ...
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
What do you like most about Microsoft Azure Machine Learning Studio?
The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem.
What is your experience regarding pricing and costs for Microsoft Azure Machine Learning Studio?
Pricing is considered to be top-segment and should be improved. I rate the pricing as three or four on a scale of one to ten in terms of affordability.
 

Also Known As

No data available
Azure Machine Learning, MS Azure Machine Learning Studio
 

Overview

 

Sample Customers

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Walgreens Boots Alliance, Schneider Electric, BP
Find out what your peers are saying about H2O.ai vs. Microsoft Azure Machine Learning Studio and other solutions. Updated: April 2025.
848,716 professionals have used our research since 2012.