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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 January 2026, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 4.6%, down from 7.6% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.9%, 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 SageMaker4.6%
SAP Predictive Analytics0.9%
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.
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

"They are doing a good job of evolving."
"They offer insights into everyone making calls in my organization."
"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"It's user-friendly for business teams as they can understand many aspects through the AWS interface."
"The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."
"The product aggregates everything we need to build and deploy machine learning models in one place."
"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."
"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 product must provide better documentation."
"The solution needs to be cheaper since it now charges per document for extraction."
"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."
"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."
"There is room for improvement in the collaboration with serverless architecture, particularly integration with AWS Lambda."
"SageMaker would be improved with the addition of reporting services."
"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."
"Lacking in some machine learning pipelines."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."
"The support costs are 10% of the Amazon fees and it comes by default."
"The pricing is comparable."
"I would rate the solution's price a ten out of ten since it is very high."
"Databricks solution is less costly than Amazon SageMaker."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."
"Amazon SageMaker is a very expensive product."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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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.
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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.
881,082 professionals have used our research since 2012.