We performed a comparison between Amazon SageMaker 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 few projects we have done have been promising."
"They are doing a good job of evolving."
"We were able to use the product to automate processes."
"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."
"Allows you to create API endpoints."
"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"RapidMiner for Windows is an excellent graphical tool for data science."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"The best part of RapidMiner is efficiency."
"I've been using a lot of components from the Strategic Extension and Python Extension."
"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."
"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 payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"The solution is complex to use."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."
"SageMaker would be improved with the addition of reporting services."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"The solution requires a lot of data to train the model."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"If they could include video tutorials, people would find that quite helpful."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"I think that they should make deep learning models easier."
"The price of this solution should be improved."
"It would be helpful to have some tutorials on communicating with Python."
"RapidMiner can improve deep learning by enhancing the features."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
Amazon SageMaker is ranked 5th in Data Science Platforms with 18 reviews while RapidMiner is ranked 7th in Data Science Platforms with 19 reviews. Amazon SageMaker is rated 7.2, while RapidMiner is rated 8.6. The top reviewer of Amazon SageMaker writes "Easy to use and manage, but the documentation does not have a lot of information". 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". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Microsoft Azure Machine Learning Studio, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and H2O.ai. See our Amazon SageMaker vs. RapidMiner report.
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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.
