Amazon SageMaker vs SAP Predictive Analytics comparison

Amazon Web Services (AWS) and SAP are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #2 with an average rating of 8.0, while SAP is ranked #27. Amazon Web Services (AWS) holds a 6.5% mindshare in Data Science Platforms, compared to SAP’s 0.4% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of SAP users who would recommend it.

Amazon SageMaker

Read 37 Amazon SageMaker reviews

5,230 Views
1,674 Comparison Views

91% willing to recommend

SAP Predictive Analytics

Read 3 SAP Predictive Analytics reviews

279 Views
89 Comparison Views

100% willing to recommend

Amazon SageMaker

SAP Predictive Analytics

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Executive SummaryUpdated on Dec 5, 2024

SAP Predictive Analytics and Amazon SageMaker are competing in the analytics solutions category. Amazon SageMaker has a competitive advantage due to its computational flexibility and AWS integration, whereas its machine learning features are particularly notable.

Features: SAP Predictive Analytics focuses on data integration, automation, and predictive modeling tools within enterprise systems. These are particularly useful for SAP ecosystem users. Amazon SageMaker enhances machine learning workflows, provides a comprehensive suite for developing, training, and deploying ML models, and supports proprietary ML projects effectively.

Ease of Deployment and Customer Service: SAP Predictive Analytics integrates seamlessly into existing SAP solutions, with straightforward deployment for SAP users and robust customer service familiar to enterprise clients. Amazon SageMaker offers intuitive deployment within AWS, extensive documentation, and support that caters to cloud-native solution preferences.

Pricing and ROI: SAP Predictive Analytics requires a significant initial setup cost but offers competitive ROI when integrated into SAP systems. Amazon SageMaker, with its pay-as-you-go pricing, provides a flexible cost structure that can lead to faster ROI, especially for AWS installations. Initial costs might be lower with SageMaker, contingent on existing infrastructure investments.

To learn more, read our detailed Amazon SageMaker vs. SAP Predictive Analytics Report (Updated: June 2025).

Buyer's Guide

Amazon SageMaker vs. SAP Predictive Analytics

June 2025

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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

7.1

Number of Reviews

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.5%, down from 9.6% compared to the previous year. The mindshare of SAP Predictive Analytics is 0.4%, down from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Saurabh Jaiswal

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 ( /products/amazon-sagemaker-reviews ), such as Firehose for connecting to data pipelines, are simple to use. Tools like AWS Glue ( /products/aws-glue-reviews ) integrate well for data transformations. The Databricks ( /products/databricks-reviews ) integration aids data scientists and engineers. SageMaker is fully managed, offers high availability, flexibility with TensorFlow ( /products/tensorflow-reviews ), PyTorch ( /products/pytorch-reviews ), and MXNet ( /products/mxnet-reviews ), and comes with pre-trained algorithms for forecasting, anomaly detection, and more.

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Gary Cook

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.

Read full review

Quotes from Members

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

Pros

"We were able to use the product to automate processes."

"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 most valuable features include the ML operations that allow for designing, deploying, testing, and evaluating models."

"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."

"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."

"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."

"The deployment is very good, where you only need to press a few buttons."

"SageMaker offers functionalities like Jupyter Notebooks for development, built-in algorithms, model tuning, and options to deploy models on managed infrastructure."

More Amazon SageMaker pros

"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

"The solution is complex to use."

"The entry point can be a bit difficult. Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"One area for improvement is the pricing, which can be quite high."

"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."

"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker."

"Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

"I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox."

More Amazon SageMaker cons

"This solution works for acquired data but not live, real-time data."

Pricing and Cost Advice

"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."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

"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."

"On average, customers pay about $300,000 USD per month."

"The support costs are 10% of the Amazon fees and it comes by default."

"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."

More Amazon SageMaker pricing and cost advice

"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

12%

Manufacturing Company

Educational Organization

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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...

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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...

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What is your experience regarding pricing and costs for Amazon SageMaker?

The pricing is high, around an eight. However, SageMaker offers free trials for the first two months, allowing users to determine which features they need. It is considered value for money given it...

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Compared 13% of the time

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Compared 100% of the time

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Product Reports

Buyer's Guide

Amazon SageMaker

June 2025

Download Amazon SageMaker product report

Buyer's Guide

Data Science Platforms

June 2025

Download SAP Predictive Analytics product report

Also Known As

AWS SageMaker, SageMaker

SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA

Overview

Amazon SageMaker is a fully-managed platform that 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.

Amazon Web Services (AWS)

SAP® Predictive Analytics software brings predictive insight to business users, analysts, data scientists, and developers in your company. Unlock the potential of Big Data from virtually any source with the power of predictive automation. By automating the building and management of sophisticated predictive models to deliver insight in real time, this software makes it easier to make better, more profitable decisions across the enterprise.

SAP

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

mBank

Buyer's Guide

Amazon SageMaker vs. SAP Predictive Analytics

June 2025

Free Report: Amazon SageMaker vs. SAP Predictive Analytics

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