We performed a comparison between Amazon SageMaker and SAS Enterprise Miner 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 tool makes our ML model development a bit more efficient because everything is in one environment."
"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."
"Allows you to create API endpoints."
"We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"They are doing a good job of evolving."
"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."
"Good data management and analytics."
"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The solution is very good for data mining or any mining issues."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"The most valuable feature is the decision tree creation."
"The technical support is very good."
"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."
"he solution is scalable."
"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 needs to be cheaper since it now charges per document for extraction."
"The product must provide better documentation."
"The training modules could be enhanced. We had to take in-person training to fully understand SageMaker, and while the trainers were great, I think more comprehensive online modules would be helpful."
"SageMaker would be improved with the addition of reporting services."
"The documentation must be made clearer and more user-friendly."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The user interface of the solution needs improvement. It needs to be more visual."
"The product must provide better integration with cloud-native technologies."
"The ease of use can be improved. When you are new it seems a bit complex."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The initial setup is challenging if doing it for the first time."
"Technical support could be improved."
"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."
Amazon SageMaker is ranked 5th in Data Science Platforms with 19 reviews while SAS Enterprise Miner is ranked 16th in Data Science Platforms with 13 reviews. Amazon SageMaker is rated 7.4, while SAS Enterprise Miner is rated 7.6. 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 SAS Enterprise Miner writes "A stable product that is easy to deploy and can be used for structured and unstructured data mining". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and Dataiku, whereas SAS Enterprise Miner is most compared with SAS Visual Analytics, IBM SPSS Modeler, RapidMiner, Microsoft Azure Machine Learning Studio and KNIME. See our Amazon SageMaker vs. SAS Enterprise Miner report.
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