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Amazon SageMaker vs SAP Predictive Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Amazon SageMaker
Ranking in Data Science Platforms
2nd
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
38
Ranking in other categories
AI Development Platforms (4th)
SAP Predictive Analytics
Ranking in Data Science Platforms
27th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 5.0%, down from 7.6% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
Amazon SageMaker5.0%
SAP Predictive Analytics0.7%
Other94.3%
Data Science Platforms
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
Python AWS & AI Expert at a tech consulting company
Create innovative assistants with seamless data integration for large-scale projects
The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue integrate well for data transformations. The Databricks integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow, PyTorch, and MXNet, and comes with pre-trained algorithms for forecasting, anomaly detection, and more.
AR
Senior Practice Manager - Head of SAP at a tech consulting company with 201-500 employees
Easy to implement, good data forecasting and reporting
This solution works for acquired data but not live, real-time data. If we connect it to a live backend system then we cannot perform predictive analytics on top of that. We have to first upload data to the cloud, manage the staging environment, and then perform the analysis. In the next release of this solution, I would like to see more automation in generating the models. The system can suggest the dimensions and measures that should be used, and pre-populate some of the information based on that. Power users would not have as much need for this, but this type of automation would be very helpful for business end-users.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."
"The support is very good with well-trained engineers whose training curriculum is rigorous."
"SageMaker is a comprehensive platform where I can perform all machine learning activities."
"The technical support of the tool was good."
"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."
"The tangible benefits we have observed from using Amazon SageMaker include improved time to insight and generally the common stack that is easier to support over time."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"The most valuable features are the analytics and reporting."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
 

Cons

"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."
"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."
"One area for improvement is the pricing, which can be quite high."
"The solution needs to be cheaper since it now charges per document for extraction."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"Databricks solution is less costly than Amazon SageMaker."
"There is no license required for the solution since you can use it on demand."
"Amazon SageMaker is a very expensive product."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"On average, customers pay about $300,000 USD per month."
"The product is expensive."
"The support costs are 10% of the Amazon fees and it comes by default."
"The pricing is reasonable"
"A free trial version is available for testing out this solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
11%
Manufacturing Company
9%
University
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise11
Large Enterprise16
No data available
 

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
What do you like most about Amazon SageMaker?
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 t...
What is your experience regarding pricing and costs for Amazon SageMaker?
If you manage it effectively, their pricing is reasonable. It's similar to anything in the cloud; if you don't manage it properly, it can be expensive, but if you do, it's fine.
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Also Known As

AWS SageMaker, SageMaker
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
mBank
Find out what your peers are saying about Amazon SageMaker vs. SAP Predictive Analytics and other solutions. Updated: December 2025.
879,310 professionals have used our research since 2012.