We performed a comparison between Dataiku and KNIME 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."Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"The solution is quite stable."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"Data Science Studio's data science model is very useful."
"The most valuable feature is the set of visual data preparation tools."
"KNIME is easy to learn."
"Overall KNIME serves its purpose and does a good job."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"It's a coding-less opportunity to use AI. This is the major value for me."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"This solution is easy to use and it can be used to create any kind of model."
"Stability is excellent. I would give it a nine out of ten."
"I think it would help if Data Science Studio added some more features and improved the data model."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"The ability to have charts right from the explorer would be an improvement."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end."
"KNIME is not good at visualization."
"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."
"System resource usage. Knime will occupy total system RAM size and other applications will hang."
"The documentation needs a proper rework. "
"KNIME could improve when it comes to large data markets."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"From the point of view of the interface, they can do a little bit better."
Dataiku is ranked 11th in Data Science Platforms while KNIME is ranked 4th in Data Science Platforms with 50 reviews. Dataiku is rated 8.2, while KNIME is rated 8.2. The top reviewer of Dataiku writes "The model is very useful". On the other hand, the top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". Dataiku is most compared with Databricks, Alteryx, RapidMiner, Microsoft Azure Machine Learning Studio and Amazon SageMaker, whereas KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx, Weka and IBM SPSS Modeler. See our Dataiku vs. KNIME report.
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