We performed a comparison between Amazon SageMaker and Google Cloud AI Platform based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution is easy to scale...The documentation and online community support have been sufficient for us so far."
"The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases."
"The deployment is very good, where you only need to press a few buttons."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"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."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"The few projects we have done have been promising."
"We were able to use the product to automate processes."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"The initial setup is very straightforward."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."
"The product must provide better documentation."
"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."
"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."
"The solution requires a lot of data to train the model."
"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."
"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."
"AI is a new area and AWS needs to have an internship training program available."
"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 think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite."
"Customizations are very difficult, and they take time."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"The solution can be improved by simplifying the process to make your own models."
"The initial setup was straightforward for me but could be difficult for others."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
Amazon SageMaker is ranked 5th in AI Development Platforms with 18 reviews while Google Cloud AI Platform is ranked 6th in AI Development Platforms with 7 reviews. Amazon SageMaker is rated 7.2, while Google Cloud AI Platform is rated 7.8. 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 Google Cloud AI Platform writes "An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data". Amazon SageMaker is most compared with Databricks, Azure OpenAI, Google Vertex AI, Domino Data Science Platform and KNIME, whereas Google Cloud AI Platform is most compared with Microsoft Azure Machine Learning Studio, IBM Watson Machine Learning, Google Vertex AI, Azure OpenAI and OpenVINO. See our Amazon SageMaker vs. Google Cloud AI Platform report.
See our list of best AI Development Platforms vendors.
We monitor all AI Development 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.
