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H2O.ai vs SAP Predictive Analytics 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)
SAP Predictive Analytics
Ranking in Data Science Platforms
25th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2025, in the Data Science Platforms category, the mindshare of H2O.ai is 1.5%, down from 1.6% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.4%, down from 0.5% 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…
Gary Cook - PeerSpot reviewer
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

Quotes from Members

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

Pros

"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."
"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."
"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 ease of use in connecting to our cluster machines."
"The most valuable features are the analytics and reporting."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
 

Cons

"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."
"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."
"The model management features could be improved."
"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."
"This solution works for acquired data but not live, real-time data."
 

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."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
11%
Manufacturing Company
10%
Energy/Utilities Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

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 ...
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Also Known As

No data available
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Learn More

 

Overview

 

Sample Customers

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
mBank
Find out what your peers are saying about H2O.ai vs. SAP Predictive Analytics and other solutions. Updated: January 2025.
831,265 professionals have used our research since 2012.