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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
28th
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 February 2026, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 4.3%, down from 7.6% compared to the previous year. The mindshare of SAP Predictive Analytics is 1.2%, 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 SageMaker4.3%
SAP Predictive Analytics1.2%
Other94.5%
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.
Gary Cook - PeerSpot reviewer
Executive at Empowered Analytics
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

Quotes from Members

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

Pros

"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"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 these models, making accessing them convenient as needed."
"The most valuable features are the ability to store artifacts and gather reports and measures from experiments."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"I have seen a return on investment, probably a factor of four or five."
"We were able to use the product to automate processes."
"They offer insights into everyone making calls in my organization."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
"The most valuable features are the analytics and reporting."
 

Cons

"One area for improvement is the pricing, which can be quite high."
"There are other better solutions for large data, such as Databricks."
"The user interface (UI) and user experience (UX) of SageMaker and AWS, in general, need improvement as they are not intuitive and require substantial time to learn how to use specific services."
"There is room for improvement in the collaboration with serverless architecture, particularly integration with AWS Lambda."
"AI is a new area and AWS needs to have an internship training program available."
"The solution requires a lot of data to train the model."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"The solution is relatively cheaper."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."
"I would rate the solution's price a ten out of ten since it is very high."
"The support costs are 10% of the Amazon fees and it comes by default."
"Databricks solution is less costly than Amazon SageMaker."
"The tool's pricing is reasonable."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"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
10%
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 Enterprise17
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.
Ask a question
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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.
881,707 professionals have used our research since 2012.