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."We were able to use the product to automate processes."
"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"The tool makes our ML model development a bit more efficient because everything is in one environment."
"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"Allows you to create API endpoints."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"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."
"The solution is very good for data mining or any mining issues."
"The most valuable feature is the decision tree creation."
"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."
"The technical support is very good."
"I like the way the product visually shows the data pipeline."
"The solution is able to handle quite large amounts of data beautifully."
"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"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."
"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."
"SageMaker would be improved with the addition of reporting services."
"The solution needs to be cheaper since it now charges per document for extraction."
"The documentation must be made clearer and more user-friendly."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"The product must provide better documentation."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"The user interface of the solution needs improvement. It needs to be more visual."
"The ease of use can be improved. When you are new it seems a bit complex."
"The visualization of the models is not very attractive, so the graphics should be improved."
"The solution is much more complex than other options."
"Technical support could be improved."
"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."
"The product must provide better integration with cloud-native technologies."
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 Microsoft Azure Machine Learning Studio, 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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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.
