H2O.ai vs SAP Predictive Analytics comparison

H2O.ai and SAP are both solutions in the Data Science Platforms category. H2O.ai is ranked #16 with an average rating of 8.0, while SAP is ranked #27. H2O.ai holds a 1.8% mindshare in Data Science Platforms, compared to SAP’s 0.5% mindshare. Additionally, 100% of H2O.ai users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

H2O.ai

Read 10 H2O.ai reviews

1,186 Views
1,115 Comparison Views

100% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

299 Views
293 Comparison Views

100% willing to recommend

H2O.ai

SAP Predictive Analytics

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Executive SummaryUpdated on Dec 5, 2024

SAP Predictive Analytics and H2O.ai compete in predictive analytics, each with distinct strengths. H2O.ai seems to have an edge with advanced machine learning frameworks and flexibility, providing better value in feature-rich environments.

Features: SAP Predictive Analytics integrates well within the SAP ecosystem, facilitating workflow simplification and automated predictive model creation for SAP users. H2O.ai offers open-source machine learning, scalability with big data, and integration support with R and Python, allowing for customizable machine learning operations.

Ease of Deployment and Customer Service:SAP Predictive Analytics provides cohesive integration within its suite, making deployment smoother for existing SAP users. H2O.ai offers flexible deployment options on various platforms with strong community and support, yielding more adaptability in diverse environments compared to SAP's integrated approach.

Pricing and ROI:SAP Predictive Analytics involves higher setup costs but offers high ROI for SAP-invested businesses by reducing operational disruptions. H2O.ai has a lower entry cost, appealing to organizations with established analytical infrastructures, achieving strong ROI through scalability and a comprehensive feature set, often proving more cost-efficient with better long-term returns.

To learn more, read our detailed H2O.ai vs. SAP Predictive Analytics Report (Updated: July 2025).

Buyer's Guide

H2O.ai vs. SAP Predictive Analytics

July 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

H2O.ai

Ranking in Data Science Platforms

16th

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Model Monitoring (4th)

SAP Predictive Analytics

Ranking in Data Science Platforms

27th

Average Rating

8.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of H2O.ai is 1.8%, up from 1.4% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.5%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Abhay Vyas

Technical Architect Data Engineering at Cognida.ai

Advanced model selection and time efficiency meet needs but documentation and fusion model support are needed

Even though H2O.ai provides the best model, there could be improvements in certain areas. For instance, when you want to work with fusion models, H2O.ai doesn't provide that kind of information. Currently, it provides individual models as outcomes. If it could offer combinations of models, such as suggesting using XGBoost along with SVM for wonderful results, that fusion model concept would be a good option for developers. I hope the fusion model concept will be implemented soon in H2O.ai. Regarding documentation, I faced challenges as I didn't see much information from a documentation perspective. When I was trying to learn how to train and test H2O.ai, there was limited documentation available. If they could improve in that area, it would be really beneficial.

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Gary Cook

Executive at Empowered Analytics

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.

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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

"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."

"H2O.ai provides better flexibility where I could examine more models and obtain results, and based on these results, I could make the next set of decisions."

"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."

"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 ease of use in connecting to our cluster machines."

"I have utilized the AutoML feature in H2O.ai, which is one of the very powerful features where you don't need to worry about which algorithm is best for your model."

More H2O.ai pros

"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

"One improvement I would like to see in H2O.ai is regarding the integration capabilities with different data sources, as I've seen platforms like DataIQ and DataBricks offer great integration with various data sources."

"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."

"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."

"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."

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

More H2O.ai cons

"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."

"The pricing is reasonable"

"A free trial version is available for testing out this solution."

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Top Industries

By visitors reading reviews

Computer Software Company

17%

Financial Services Firm

17%

Manufacturing Company

Educational Organization

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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Questions from the Community

What needs improvement with H2O.ai?

One improvement I would like to see in H2O.ai is regarding the integration capabilities with different data sources, as I've seen platforms like DataIQ and DataBricks offer great integration with v...

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What is your primary use case for H2O.ai?

Normally, I use H2O.ai for my machine learning tasks, and to give an example, some of the models that I've created using H2O.ai are taxi demand forecasting and a scoring model for leads. Most of my...

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What advice do you have for others considering H2O.ai?

I would rate the technical support a nine. For organizations considering H2O.ai, my recommendations include appreciating it as a great and flexible tool for machine learning tasks without incurring...

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Comparisons

Dataiku vs H2O.ai

Compared 24% of the time

Amazon SageMaker vs H2O.ai

Compared 19% of the time

Databricks vs H2O.ai

Compared 18% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 15% of the time

More H2O.ai Competitors

KNIME Business Hub vs SAP Predictive Analytics

Compared 28% of the time

Microsoft Azure Machine Learning Studio vs SAP Predictive Analytics

Compared 28% of the time

IBM SPSS Statistics vs SAP Predictive Analytics

Compared 22% of the time

More SAP Predictive Analytics Competitors

Product Reports

Buyer's Guide

Data Science Platforms

August 2025

Download H2O.ai product report

Buyer's Guide

Data Science Platforms

August 2025

Download SAP Predictive Analytics product report

Also Known As

No data available

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

Overview

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

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

SAP

Sample Customers

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

mBank

Buyer's Guide

H2O.ai vs. SAP Predictive Analytics

July 2025

Free Report: H2O.ai vs. SAP Predictive Analytics

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