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 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."
"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"We've had no problems with SageMaker's stability."
"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 solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"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 most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."
"The technical support is very good."
"The solution is able to handle quite large amounts of data beautifully."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"he solution is scalable."
"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."
"I like the way the product visually shows the data pipeline."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"The documentation must be made clearer and more user-friendly."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"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 pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"The solution needs to be cheaper since it now charges per document for extraction."
"There are other better solutions for large data, such as Databricks."
"The visualization of the models is not very attractive, so the graphics should 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 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."
"The initial setup is challenging if doing it for the first time."
"The product must provide better integration with cloud-native technologies."
"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."
"Technical support could be improved."
"The ease of use can be improved. When you are new it seems a bit complex."
Amazon SageMaker is ranked 5th in Data Science Platforms with 18 reviews while SAS Enterprise Miner is ranked 14th in Data Science Platforms with 13 reviews. Amazon SageMaker is rated 7.2, 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 SAS Analytics. See our Amazon SageMaker vs. SAS Enterprise Miner report.
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