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."They are doing a good job of evolving."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."
"Allows you to create API endpoints."
"We were able to use the product to automate processes."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"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."
"The data science, collaboration, and IDN are very, very strong."
"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."
"RapidMiner for Windows is an excellent graphical tool for data science."
"The GUI capabilities of the solution are excellent. Their Auto ML model provides for even non-coder data scientists to deploy a model."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"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."
"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"The product must provide better documentation."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"SageMaker would be improved with the addition of reporting services."
"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."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"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."
"I would appreciate improvements in automation and customization options to further streamline processes."
"Improve the online data services."
"In terms of the UI and SaaS, the user interface with KNIME is more appealing than RapidMiner."
"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."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"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."
"I would like to see more integration capabilities."
"The price of this solution should be improved."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while RapidMiner is ranked 6th in Data Science Platforms with 20 reviews. Amazon SageMaker is rated 7.4, 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 "A no-code tool that helps to build machine learning models ". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Dataiku, whereas RapidMiner is most compared with KNIME, Alteryx, Dataiku, Tableau and H2O.ai. See our Amazon SageMaker vs. RapidMiner report.
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