We performed a comparison between H2O.ai and KNIME based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"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."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"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 ease of use in connecting to our cluster machines."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"It is a stable solution...It is a scalable solution."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"There are a lot of connectors available in KNIME."
"Stability is excellent. I would give it a nine out of ten."
"The most useful features are the readily available extensions that speed up the work."
"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."
"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."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"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."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"The model management features could be improved."
"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."
"From the point of view of the interface, they can do a little bit better."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"The documentation is lacking and it could be better."
"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."
"They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning."
Earn 20 points
H2O.ai is ranked 19th in Data Science Platforms while KNIME is ranked 4th in Data Science Platforms with 50 reviews. H2O.ai is rated 7.6, while KNIME 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 KNIME writes "A low-code platform that reduces data mining time by linking script". H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and IBM Watson Studio, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and Domino Data Science Platform.
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