Try our new research platform with insights from 80,000+ expert users

Alteryx vs H2O.ai 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

Alteryx
Ranking in Data Science Platforms
5th
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
81
Ranking in other categories
Predictive Analytics (1st), Data Preparation Tools (1st)
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)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Alteryx is 6.2%, down from 8.0% compared to the previous year. The mindshare of H2O.ai is 1.5%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

Theresa McLaughlin - PeerSpot reviewer
Quick development enables seamless data processing despite occasional support issues
There were times when the product would fail during development without an apparent reason. The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system. Licensing negotiations were problematic, affecting our product usage. For instance, our licenses were temporarily lost during negotiations when an agreement couldn't be reached.
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…

Quotes from Members

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

Pros

"The design portion of this tool is easy to use without code, which his something that something we can appreciate."
"I found Alteryx's ability to modify data on the fly, using in-memory processing, very useful."
"One-stop shop for data preparation, blending, prediction, and optimization in a single workflow."
"It is a stable and scalable solution."
"Good data transformation."
"Alteryx makes it easy for the end customer to see clean data in a structured form."
"The cloud deployment ensures it scales easily."
"I like the fact that you can easily blend data from different platforms."
"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 features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"The ease of use in connecting to our cluster machines."
"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."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"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."
 

Cons

"They should make the solution user-friendly for nontechnical people by giving specific names to the options."
"The screen when you are looking into your workflows and your ETL processes needs to be improved. You cannot manage it very well."
"When configuring target tables, it is difficult to see the full text when deciding on load operations."
"The solution just lacks in terms of data visualization. That is why we use Tableau and Qlik in our organization. They help to pick up the slack. If data visualization was added, Alteryx would be a very good tool, and much more complete."
"The software is not fully optimized."
"Alteryx could be improved in the area of analytics and central governance."
"There's a big jump in terms of pricing between license tiers. I'm not sure I understand why the price jumps are so high."
"The next feature release should include easier reporting."
"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."
"H2O.ai can improve in areas like multimodal support and prompt engineering."
"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."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"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."
 

Pricing and Cost Advice

"The pricing is $5000 per year per production license."
"If one is a high price, and ten is a low price, I rate the tool's price as a one. The tool is expensive."
"My organization pays for it, and I do not look into the financial aspect of the licensing, but I know it is pretty expensive."
"There is a license required for this solution."
"In order to have designers, and, if you want to collaborate, you have to buy a server. If the designer is $5,000, and if you want a server, you have to pay $80,000."
"The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area."
"While it offers extensive features, including predictive analytics, for those who mainly use it for data preparation and blending, the cost can be prohibitive."
"It's very expensive. I'd rate it a four out of ten in terms of the price. It's great for big companies but not for small companies."
"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."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
842,767 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
24%
Manufacturing Company
10%
Computer Software Company
9%
Healthcare Company
6%
Financial Services Firm
21%
Computer Software Company
11%
Manufacturing Company
9%
Energy/Utilities Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
One of the differences is that with Alteryx you can use it as an ETL and analytics tool. Please connect with me directly if you want to know more.
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
Alteryx is an extremely easy and flexible data tool, flexible in terms of drag and drop toolset and also has python, R integrations if your team requires this. It can handle over 2 billion rows of...
What is the Biggest Difference Between Alteryx and IBM SPSS Modeler?
I am not familiar with IBM SPSS Modeler, therefore, I cannot compare these two products. Regarding Alteryx I can say the following: - An excellent desktop tool for Data Prep and analytics. - Featu...
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 ...
 

Comparisons

 

Overview

 

Sample Customers

AnalyticsIq Inc., belk, BloominBrands Inc., Cardinalhealth, Cineplex, Dairy Queen
poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
Find out what your peers are saying about Alteryx vs. H2O.ai and other solutions. Updated: March 2025.
842,767 professionals have used our research since 2012.