We performed a comparison between H2O.ai and IBM Watson Studio based on real PeerSpot user reviews.
Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"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."
"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."
"AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"It is a stable, reliable product."
"The scalability of IBM Watson Studio is great."
"The solution is very easy to use."
"Watson Studio is very stable."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"The system's ability to take a look at data, segment it and then use that data very differently."
"Stability-wise, it is a great tool."
"The model management features could be improved."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"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 main challenge lies in visibility and ease of use."
"The decision making in their decision making feature is less good than other options."
"We would like to see it more web-based with more functionality."
"The solution's interface is very slow at times."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"I want IBM's technical support team to provide more specific answers to queries."
"The initial setup was complex."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
Earn 20 points
H2O.ai is ranked 20th in Data Science Platforms while IBM Watson Studio is ranked 10th in Data Science Platforms with 13 reviews. H2O.ai is rated 7.6, while IBM Watson Studio is rated 8.2. The top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". On the other hand, the top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku, Microsoft Azure Machine Learning Studio and RapidMiner, whereas IBM Watson Studio is most compared with Databricks, Azure OpenAI, Microsoft Azure Machine Learning Studio, Google Vertex AI and IBM Watson OpenScale. See our H2O.ai vs. IBM Watson Studio report.
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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.
