We performed a comparison between Alteryx and H2O.ai 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."The product's Macros probably are one of the most useful aspects."
"One-stop shop for data preparation, blending, prediction, and optimization in a single workflow."
"The connectors are a very good feature."
"Alteryx has a good UI. We use it frequently in our projects. The tool comes with drag-and-drop features and is easy to understand for business needs. One situation where Alteryx's advanced analytics capabilities were particularly beneficial for us was during a forecasting project. Unlike Python, which requires coding, Alteryx simplifies the process significantly. With Alteryx, users can adjust parameters within the user interface without writing any code."
"My primary focus is creating numerous data pulls, and Alteryx Server handles the automation well."
"The solution has excellent drag and drop functionality. There's no need for coding."
"The Alteryx designer has been the most useful feature in the solution."
"The most valuable feature of Alteryx is its performance. It is a powerful solution."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"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."
"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 ease of use in connecting to our cluster machines."
"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 workflow and pipeline need to improve."
"Lacks an open source edition which would be helpful."
"Alteryx could be improved in the area of analytics and central governance."
"A colleague of mind mentioned that the solution should have more options for the visualization of data."
"I think they should really work on integrating or have a capacity to integrate some algorithmic code. I think that's one of the most important things they need to be doing."
"We can't browse multiple files. When we deploy a solution on a gallery, let's say I have ten different files, and I have to upload them all at once. This is something that's difficult in the gallery. So case by case, I see some downsides, but often we do something alternative."
"What they're struggling with is it's not as mature as Tableau in the user management area. It was tougher to manage the server part of it right away, especially since the user base has grown."
"Sometimes workflows tend to queue up, and they tend to get canceled for some reason that we don't know sometimes."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"I would like to see more features related to deployment."
"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."
"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."
"The model management features could be improved."
Earn 20 points
Alteryx is ranked 3rd in Data Science Platforms with 74 reviews while H2O.ai is ranked 20th in Data Science Platforms. Alteryx is rated 8.4, while H2O.ai is rated 7.6. The top reviewer of Alteryx writes "Feature-rich ETL that condenses a number of functions into one tool". On the other hand, the top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". Alteryx is most compared with KNIME, Databricks, Dataiku, RapidMiner and Microsoft Power BI, whereas H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku, Microsoft Azure Machine Learning Studio and Domino Data Science Platform. See our Alteryx vs. H2O.ai report.
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