Amazon SageMaker vs. SAP Predictive Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon SageMaker
Score 8.3 out of 10
N/A
Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.N/A
SAP Predictive Analytics
Score 7.0 out of 10
N/A
SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.N/A
Pricing
Amazon SageMakerSAP Predictive Analytics
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Amazon SageMakerSAP Predictive Analytics
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon SageMakerSAP Predictive Analytics
Top Pros
Top Cons
Best Alternatives
Amazon SageMakerSAP Predictive Analytics
Small Businesses
Google Cloud AI
Google Cloud AI
Score 8.3 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Google Cloud AI
Google Cloud AI
Score 8.3 out of 10
Alteryx
Alteryx
Score 9.0 out of 10
Enterprises
Dataiku
Dataiku
Score 7.9 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon SageMakerSAP Predictive Analytics
Likelihood to Recommend
9.0
(6 ratings)
9.0
(3 ratings)
Usability
-
(0 ratings)
6.0
(1 ratings)
Support Rating
-
(0 ratings)
7.0
(1 ratings)
User Testimonials
Amazon SageMakerSAP Predictive Analytics
Likelihood to Recommend
Amazon AWS
Amazon SageMaker is a great tool for developing machine learning models that take more effort than just point-and-click type of analyses. The software works well with the other tools in the Amazon ecosystem, so if you use Amazon Web Services or are thinking about it, SageMaker would be a great addition. SageMaker is great for consumer insights, predictive analytics, and looking for gems of insight in the massive amounts of data we create. SageMaker is less suitable for analysts who do generally "small" data analyses, and "small" data analyses in today's world can be billions of records.
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SAP
It's a great tool to merge actual data analysis (which Lumira doesn't do that well) with visualization (which Lumira does well) - so it can be seen as Lumira for data analysts. However, a lot of the 'predictive' side is hidden/black box which can be frustrating for those analysts, so you could argue it is too complex for casual users, but too 'black box' for analysts.
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Pros
Amazon AWS
  • Provides enough freedom for experienced data scientists and also for those who just need things done without going much deeper into building models.
  • Customization and easy to alter and change.
  • If you already are an Amazon user, you do not need to transition over to another software.
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SAP
  • It doesn't require you to have a Ph.D. to build models!
  • You can use it to address a very large and wide dataset without worrying about sampling.
  • Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.
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Cons
Amazon AWS
  • The UI can be eased up a bit for use by business analysts and non technical users
  • For huge amount of data pull from legacy solutions, the platform lags a bit
  • Considering ML is an emerging topic and would be used by most of the organizations in future, the pipeline integrations can be optimized
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SAP
  • Working with this software is very simple and enjoyable for me as [an] IT consultant and expert, but it is a bit complicated for novice users.
  • Some big data takes more time‌to load, which I think could be faster
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Usability
Amazon AWS
No answers on this topic
SAP
the UI is a bit dated and available as a desktop tool mostly.
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Support Rating
Amazon AWS
No answers on this topic
SAP
The documentation provides an explanation about what features are available but not necessarily what's happening behind the scenes. On the other side, the "community" has grown since the acquisition and most questions are properly addressed by SAP folks. Since the "product maintenance" mode announcement was made, there wasn't much new content published except on the Smart Predict side (which is built by the SAP Predictive Analytics team)
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Alternatives Considered
Amazon AWS
Amazon SageMaker comes with other supportive services like S3, SQS, and a vast variety of servers on EC2. It's very comfortable to manage the process and also support the end application by one click hosting option. Also, it charges on the base of what you use and how long you use it, so it becomes less costly compared to others.
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SAP
We have typically used Spotfire for data analysis but decided to move to SAP Business Objects due to its innate connection with SAP. I found Lumira to be good for visualizations but it is not meant for data analysis. Therefore, we have introduced Predictive Analytics to see if it can fill that gap. So far, it's been far less intuitive than Spotfire to get started, and as far as I am aware so far, it does not bring many additional capabilities. I do, however, like that it utilizes the Lumira look/feel and integrates very well.
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Return on Investment
Amazon AWS
  • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
  • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
  • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
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SAP
  • Proper forecasting increases our credibility with partners and customers
  • Forecasting determines the amount of investment in each sector and reduces the cost of additional costs
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ScreenShots