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H2O.ai vs Microsoft Azure Machine Learning Studio comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
H2O.ai
Ranking in Data Science Platforms
22nd
Average Rating
7.6
Number of Reviews
8
Ranking in other categories
Model Monitoring (8th)
Microsoft Azure Machine Lea...
Ranking in Data Science Platforms
3rd
Average Rating
7.8
Number of Reviews
57
Ranking in other categories
AI Development Platforms (2nd)
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. 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 6.0%, down from 12.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Enhancing survey analysis that provides valued insightfulness
I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.
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…
Klaus Lozie - PeerSpot reviewer
Provides good integration and used for data labeling
Lately, we have had some issues with the solution regarding labeling jobs. We can create a label job, but we still have to use the Azure Machine Learning REST APIs, which are not yet supported in the Python SDK version 2. Microsoft has a lot of documentation, but you can do it using the CLI, UI, or Python SDK version 2. You can have 100 ways of working, while I would like to have one way of working. It's very difficult to know what is best, according to Microsoft.

Quotes from Members

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

Pros

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."
"The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."
"in terms of the simplicity, I think the SPSS basic can handle it."
"IBM SPSS Statistics depends on AI."
"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 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."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"The solution facilitates our production."
"The product supports open-source tools."
"ML Studio is very easy to maintain."
"​It has helped in reducing the time involved for coding using R and/or Python."
"The most valuable feature of this solution is the ability to use all of the cognitive services, prebuilt from Azure."
"Visualisation, and the possibility of sharing functions are key features."
"The drag-and-drop interface of Azure Machine Learning Studio has greatly improved my workflow."
"Its ability to publish a predictive model as a web based solution and integrate R and python codes are amazing."
 

Cons

"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"In some cases, the product takes time to load a large dataset. They could improve this particular area."
"The reports could be better."
"The technical support should be improved."
"The statistics should be more self-explanatory with detailed automated reports."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"The solution needs to improve forecasting using time series analysis."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
"I would like to see more features related to deployment."
"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."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"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 needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"The model management features could be improved."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"Integration with social media would be a valuable enhancement."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"Enable creating ensemble models easier, adding more machine learning algorithms."
"It would be nice if the product offered more accessibility in general."
"In the future, I would like to see more AI consultation like image and video classification, and improvement in the presentation of data."
"Using the solution requires some specific learning which can take some time."
"The speed of deployment should be faster, as should testing."
"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."
 

Pricing and Cost Advice

"More affordable training for new staff members."
"The price of this solution is a little bit high, which was a problem for my company."
"We think that IBM SPSS is expensive for this function."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"The price of IBM SPSS Statistics could improve."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"It's quite expensive, but they do a special deal for universities."
"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."
"I am paying for it following a pay-as-you-go. So, the more I use it, the more it costs."
"The pricing for Microsoft products can be complex due to changes and being cloud-based, so it's not straightforward. I've been familiar with it for years, but sometimes details about product licenses and distribution can be unclear. For Microsoft Azure Machine Learning Studio specifically, I would rate the price a six out of ten."
"The product's pricing is reasonable."
"There is a lack of certainty with the solution's pricing."
"The product is not that expensive."
"I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap."
"From a developer's perspective, I find the price of this solution high."
"The platform's price is low."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
9%
University
9%
Manufacturing Company
8%
Financial Services Firm
20%
Computer Software Company
11%
Manufacturing Company
10%
Insurance Company
7%
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
10%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...
What needs improvement with IBM SPSS Statistics?
IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...
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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 ...
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.
 

Also Known As

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

Learn More

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
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: October 2024.
816,636 professionals have used our research since 2012.