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H2O.ai vs SAS Visual Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

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
Average Rating
7.6
Reviews Sentiment
6.8
Number of Reviews
10
Ranking in other categories
Data Science Platforms (13th), Model Monitoring (4th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
40
Ranking in other categories
Data Visualization (11th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. H2O.ai is designed for Data Science Platforms and holds a mindshare of 2.7%, up 1.5% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 1.8% mindshare, down 4.6% since last year.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
H2O.ai2.7%
Databricks9.3%
KNIME Business Hub6.8%
Other81.2%
Data Science Platforms
Data Visualization Mindshare Distribution
ProductMindshare (%)
SAS Visual Analytics1.8%
Tableau Enterprise11.0%
Domo5.7%
Other81.5%
Data Visualization
 

Featured Reviews

MA
Senior Manager - AI at Shamal Holding
Have improved machine learning model automation and reduced decision-making time
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. H2O.ai could benefit from enhanced integration with real-time versus offline data sources, as well as improvements in productionalization solutions, including better deployment options on platforms like Azure and CI/CD integration. One of the features I'd like to see included in upcoming releases of H2O.ai pertains to the growing trend of Generative AI, with applications for LLM-based models and vector databases. I would like to see a solution similar to Azure AI Foundry, which provides the flexibility to integrate different LLMs into applications, including H2O-GPT and other models for varied applications.
AN
Senior Manager: ICT Compliance at DEPARTMENT OF PUBLIC SERVICE AND ADMINISTRATION
Enables effective data management and reporting with a straightforward setup
SAS Visual Analytics is helpful as it allows us to perform any queries we need. The ability to query information from our Excel data into SAS to view specific data is invaluable. In terms of reporting, it is easy to extract quick reports and provides graphical representations of the data, which is a great feature.

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."
"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."
"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."
"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."
"The product is definitely worth looking at, as it is one of the upcoming products where you can build large models for use cases."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"Data handling is one of the best features of SAS Visual Analytics."
"I would rate the overall solution a ten out of ten."
"The speed to display charts and react to users' choices is great."
"It was helpful for creating KPI dashboards to report the status of the operations of the entire company to the management."
"The advantage of this tool is its big data handling in seconds and its predefined statistical methods for better data evaluation and understanding."
"Exposure of full population transactional data to customer facing roles with ability to analyse trends and patterns empowers our citizen data scientists to answer their own business questions regarding customer trends and to forecast future trends."
"I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data."
 

Cons

"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."
"Feature engineering."
"The model management features could be improved."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"I would like to see more features related to deployment."
"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."
"Colours used on report objects"
"It takes a lot of effort to stabilize. We need to change some hardware and configurations to stabilize the solution."
"There is no business intelligence application that is predefined, which is something some customers or prospects would love to have."
"SAS Visual Analytics was often prone to crashing. Modules with barely 20 to 30 GB datasets took a lot of time to load even after satisfying necessary software specifications (RAM, etc.)."
"The solution is a little weak at the front end."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
"Many things are missing, including Infomaps, Facebook connection, and better objects, and forecasting, auto-charting, and correlation are only available in exploration but should be available in reports."
"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."
 

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 product is quite expensive."
"The cost of the solution can be expensive. There is an additional cost for users."
"SAS Visual Analytics is expensive, as is the rest of the platform."
"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."
"Licensing is simple."
"It's approximately $114,000 US dollars per year."
"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."
"It was licensed for corporate use, and its licensing was on a yearly basis."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
9%
Manufacturing Company
7%
Educational Organization
7%
Financial Services Firm
14%
Government
10%
Construction Company
8%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise3
Large Enterprise7
By reviewers
Company SizeCount
Small Business13
Midsize Enterprise8
Large Enterprise19
 

Questions from the Community

What needs improvement with H2O.ai?
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. Cu...
What is your primary use case for H2O.ai?
I used H2O.ai on several POCs for my previous company, and it helped me find the best model. I needed to determine which model was performing better for job portal data. At that time, H2O.ai was ev...
What advice do you have for others considering H2O.ai?
For larger datasets, model computation or model training and testing typically takes considerable time because with individual models, you need to train and test each one. With H2O.ai, these concer...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI. It may be that our current subscription does not include AI-enabled features, but I wo...
What is your primary use case for SAS Visual Analytics?
I started to work with SAS Visual Analytics ( /products/sas-visual-analytics-reviews ) in 2015. We use it for analysis on ICT expenditure information and ICT personnel information. The analytics ar...
 

Also Known As

No data available
SAS BI
 

Overview

 

Sample Customers

poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: March 2026.
885,444 professionals have used our research since 2012.