We performed a comparison between Dataiku Data Science Studio and RapidMiner based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."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."
"Data Science Studio's data science model is very useful."
"The most valuable feature is the set of visual data preparation tools."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"The solution is quite stable."
"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."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"We value the collaboration and governance features because it's a comprehensive platform that covers everything from data extraction to modeling operations in the ML language. RapidMiner is competitive in the ML space."
"RapidMiner is very easy to use."
"Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The best part of RapidMiner is efficiency."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"What I like about RapidMiner is its all-in-one nature, which allows me to prepare, extract, transform, and load data within the same tool."
"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 think it would help if Data Science Studio added some more features and improved the data model."
"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."
"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)."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"The ability to have charts right from the explorer would be an improvement."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"In the Mexican or Latin American market, it's kind of pricey."
"The server product has been getting updated and continues to be better each release. When I started using RapidMiner, it was solid but not easy to set up and upgrade."
"The price of this solution should be improved."
"RapidMiner can improve deep learning by enhancing the features."
"I think that they should make deep learning models easier."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"I would like to see more integration capabilities."
Dataiku Data Science Studio is ranked 6th in Data Science Platforms while RapidMiner is ranked 7th in Data Science Platforms with 19 reviews. Dataiku Data Science Studio is rated 8.2, while RapidMiner is rated 8.6. The top reviewer of Dataiku Data Science Studio writes "The model is very useful". On the other hand, the top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". Dataiku Data Science Studio is most compared with Databricks, Alteryx, KNIME, Microsoft Azure Machine Learning Studio and Amazon SageMaker, whereas RapidMiner is most compared with KNIME, Alteryx, Tableau, Microsoft Azure Machine Learning Studio and IBM SPSS Modeler.
See our list of best Data Science Platforms vendors.
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.