We performed a comparison between H2O.ai and Teradata Analytics [EOL] based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."The ease of use in connecting to our cluster machines."
"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."
"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 features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"nPath has made journey/path analysis much easier."
"It has been fantastic for running complete data sets (no sampling required)."
"Provides ease of formulating a solution based on SQL-like queries."
"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."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"I would like to see more features related to deployment."
"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."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"We have struggled with uptime. Some of the features need to be updated."
"I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such."
"I would like to see more/better documentation. They also need to enhance analytic/data science algorithms."
H2O.ai is ranked 19th in Data Science Platforms while Teradata Analytics [EOL] doesn't meet the minimum requirements to be ranked in Data Science Platforms. H2O.ai is rated 7.6, while Teradata Analytics [EOL] is rated 7.0. 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 Teradata Analytics [EOL] writes "Streamlines formulating solutions based on SQL-like queries". H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and KNIME, whereas Teradata Analytics [EOL] is most compared with .
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