Altair Knowledge Studio vs H2O.ai comparison

Altair and H2O.ai are both solutions in the Data Science Platforms category. Altair is ranked #21 with an average rating of 8.0, while H2O.ai is ranked #20 with an average rating of 7.0. Altair holds a 0.4% mindshare in Data Science Platforms, compared to H2O.ai’s 1.7% 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

227 Views
62 Comparison Views

100% willing to recommend

H2O.ai

Read 8 H2O.ai reviews

1,152 Views
379 Comparison Views

100% willing to recommend

Altair Knowledge Studio

H2O.ai

Comparison Buyer's Guide

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Executive Summary

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

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Buyer's Guide

Data Science Platforms

June 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

Altair Knowledge Studio

Ranking in Data Science Platforms

21st

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

20th

Average Rating

7.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Model Monitoring (5th)

Mindshare comparison

As of June 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 1.7%, 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 ( /products/segment-reviews ) 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.

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Kashif Yaseen

Trainee Decision Scientist at a tech services company with 1,001-5,000 employees

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…

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

"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."

"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 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."

"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."

Cons

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

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

"The model management features could be improved."

"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."

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

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

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

"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."

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."

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

19%

Computer Software Company

13%

Manufacturing Company

10%

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.

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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...

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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 ...

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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.

See all answers

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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Comparisons

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Compared 44% of the time

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Dataiku vs H2O.ai

Compared 25% of the time

Amazon SageMaker vs H2O.ai

Compared 21% of the time

Databricks vs H2O.ai

Compared 20% of the time

Microsoft Azure Machine Learning Studio vs H2O.ai

Compared 17% of the time

KNIME vs H2O.ai

Compared 11% of the time

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Product Reports

Buyer's Guide

Data Science Platforms

June 2025

Download Altair Knowledge Studio product report

Buyer's Guide

Data Science Platforms

June 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

June 2025

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