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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 (5th)
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 September 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.0%, down from 8.5% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.5%, 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 SageMaker6.0%
SAP Predictive Analytics0.5%
Other93.5%
Data Science Platforms
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
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
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

"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."
"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 few projects we have done have been promising."
"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."
"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."
"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"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 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."
"AI is a new area and AWS needs to have an internship training program available."
"The model repository is a concern as models are stored on a bucket and there's an issue with versioning."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"The solution requires a lot of data to train the model."
"The main challenge with Amazon SageMaker is the integrations."
"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"They could add features such as managing environments, experiment management across those environments, and the integration with training datasets as you go through those experiments."
"This solution works for acquired data but not live, real-time data."
 

Pricing and Cost Advice

"The pricing could be better, especially for querying. The per-query model feels expensive."
"I would rate the solution's price a ten out of ten since it is very high."
"Amazon SageMaker is a very expensive product."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
"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."
"There is no license required for the solution since you can use it on demand."
"The tool's pricing is reasonable."
"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
19%
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: July 2025.
867,370 professionals have used our research since 2012.