Altair Knowledge Studio vs H2O.ai comparison

Altair and H2O.ai are both solutions in the Data Science Platforms category. Altair is ranked #22 with an average rating of 8.0, while H2O.ai is ranked #16 with an average rating of 8.0. Altair holds a 0.4% mindshare in Data Science Platforms, compared to H2O.ai’s 1.8% mindshare. Additionally, 100% of Altair users are willing to recommend the solution, compared to 100% of H2O.ai users who would recommend it.

Altair Knowledge Studio

Read 2 Altair Knowledge Studio reviews

255 Views
242 Comparison Views

100% willing to recommend

H2O.ai

Read 10 H2O.ai reviews

1,186 Views
1,115 Comparison Views

100% willing to recommend

Altair Knowledge Studio

H2O.ai

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Altair Knowledge Studio and H2O.ai based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms.

To learn more, read our detailed Data Science Platforms Report (Updated: August 2025).

Buyer's Guide

Data Science Platforms

August 2025

Download the complete report

Helped 865,384 peers since 2012

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

Altair Knowledge Studio

Ranking in Data Science Platforms

22nd

Average Rating

8.0

Reviews Sentiment

8.9

Number of Reviews

Ranking in other categories

No ranking in other categories

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)

Mindshare comparison

As of August 2025, in the Data Science Platforms category, the mindshare of Altair Knowledge Studio is 0.4%, up from 0.2% compared to the previous year. The mindshare of H2O.ai is 1.8%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Leo Sundararaj

Account Manager at JegaSure

Advanced decision trees and seamless data pattern analysis transform data preparation

One of the most valuable features of Altair Knowledge Studio is its decision trees, which are quite advanced and popular compared to other tools. The Segment Viewer is another unique feature that provides a comprehensive view of data patterns and helps identify anomalies before creating decision trees. Additionally, the ability to export code in the language of SAS is valuable, and the tool's drag-and-drop functionality makes it accessible to business users without a coding background.

Read full review

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.

Read full review

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 valuable features of Altair Knowledge Studio is its decision trees, which are quite advanced and popular compared to other tools."

"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."

"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."

"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."

"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 feature of H2O.ai is that it is plug-and-play."

"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."

"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."

More H2O.ai pros

Cons

"It would be beneficial if Altair Knowledge Studio could offer a more unified platform that includes data preparation, predictive modeling, and model exportation."

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

"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."

"I would like to see more features related to deployment."

"The model management features could be improved."

"H2O.ai can improve in areas like multimodal support and prompt engineering."

"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."

"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."

"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."

More H2O.ai cons

Pricing and Cost Advice

Information not available

"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."

See which vendors are best for you

Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.

See recommendations

865,384 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

No data available

Computer Software Company

17%

Financial Services Firm

17%

Manufacturing Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What is your experience regarding pricing and costs for Altair Knowledge Studio?

The licensing is straightforward, and we have not encountered any pushbacks from our procurement team. The pricing is on par with market competitors.

See all answers

What needs improvement with Altair Knowledge Studio?

It would be beneficial if Altair Knowledge Studio could offer a more unified platform that includes data preparation, predictive modeling, and model exportation. Having all these functionalities wi...

See all answers

What is your primary use case for Altair Knowledge Studio?

I used Altair Knowledge Studio ( /products/altair-knowledge-studio-reviews ) mainly for data preparation and creating decision trees. We used SAS for data preparation and decision trees in Altair K...

See all answers

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...

See all answers

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...

See all answers

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...

See all answers

Comparisons

KNIME Business Hub vs Altair Knowledge Studio

Compared 43% of the time

Altair RapidMiner vs Altair Knowledge Studio

Compared 21% of the time

Databricks vs Altair Knowledge Studio

Compared 18% of the time

MathWorks Matlab vs Altair Knowledge Studio

Compared 18% of the time

More Altair Knowledge Studio Competitors

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

KNIME Business Hub vs H2O.ai

Compared 13% of the time

More H2O.ai Competitors

Product Reports

Buyer's Guide

Data Science Platforms

August 2025

Download Altair Knowledge Studio product report

Buyer's Guide

Data Science Platforms

August 2025

Download H2O.ai product report

Also Known As

Angoss KnowledgeSTUDIO

No data available

Overview

Business intelligence and predictive analytics software suite from Angoss Software Corporation. KnowledgeSTUDIO is a market-leading business intelligence software product with data mining and predictive analytics capabilities including data profiling, advanced data visualization, advanced modeling, unsupervised learning, decision tree and strategy design functionality.

Altair

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

Sample Customers

HSBC, MBNA, US Ban Corp, MasterCard Worldwide, Invesco, Citi Bank, ATB Financial, PayPal, Bajaj Finserv

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

Buyer's Guide

Data Science Platforms

August 2025

Download Free Report

Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: August 2025.

DOWNLOAD NOW

865,384 professionals have used our research since 2012.

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.