We performed a comparison between Databricks and RapidMiner 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 initial setup is pretty easy."
"The solution is very easy to use."
"We can scale the product."
"The simplicity of development is the most valuable feature."
"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."
"The most valuable feature of Databricks is the integration with Microsoft Azure."
"It's easy to increase performance as required."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"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."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"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."
"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."
"The most valuable features are the Binary classification and Auto Model."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The most valuable feature is what the product sets out to do, which is extracting information and data."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"CI/CD needs additional leverage and support."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"I would like it if Databricks made it easier to set up a project."
"The pricing of Databricks could be cheaper."
"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"Pricing is one of the things that could be improved."
"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."
"RapidMiner isn't cheap. It's a complete solution, but it's costly."
"I would like to see more integration capabilities."
"The price of this solution should be improved."
"The visual interface could use something like the-drag-and-drop features which other products already support. Some additional features can make RapidMiner a better tool and maybe more competitive."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"If they could include video tutorials, people would find that quite helpful."
Databricks is ranked 1st in Data Science Platforms with 78 reviews while RapidMiner is ranked 7th in Data Science Platforms with 19 reviews. Databricks is rated 8.2, while RapidMiner is rated 8.6. The top reviewer of Databricks writes "A nice interface with good features for turning off clusters to save on computing". 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". Databricks is most compared with Amazon SageMaker, Informatica PowerCenter, Dataiku Data Science Studio, Microsoft Azure Machine Learning Studio and Dremio, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and SAS Enterprise Miner. See our Databricks vs. RapidMiner report.
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