Amazon SageMaker vs SAS Enterprise Miner comparison

Amazon Web Services (AWS) and SAS are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #2 with an average rating of 8.1, while SAS is ranked #23. Amazon Web Services (AWS) holds a 4.6% mindshare in Data Science Platforms, compared to SAS’s 1.6% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Amazon SageMaker

Read 38 Amazon SageMaker reviews

6,186 Views
3,588 Comparison Views

91% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,059 Views
805 Comparison Views

93% willing to recommend

Amazon SageMaker

SAS Enterprise Miner

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and Amazon SageMaker compete in the analytical and predictive modeling market. Amazon SageMaker has the upper hand due to its comprehensive integration capabilities and scalability.

Features: SAS Enterprise Miner provides robust data manipulation, in-depth statistical analysis, and decision tree creation. It supports rich model diagnostics, visual data exploration, and seamless data processing. Amazon SageMaker offers seamless AWS integration, model deployment services, and automated hyperparameter tuning. It supports built-in algorithms, Jupyter Notebooks, and advanced model monitoring.

Room for Improvement: SAS Enterprise Miner can enhance its scalability and integration capabilities, improve cloud integration, and offer more diverse language support. Amazon SageMaker could improve user-friendliness for non-experts, reduce dependency on AWS infrastructure, and expand initial training resources for beginners.

Ease of Deployment and Customer Service: Amazon SageMaker leverages AWS's cloud infrastructure for rapid deployment and efficiency, benefiting from AWS's extensive support. SAS Enterprise Miner requires traditional installations but offers dedicated customer support for its users.

Pricing and ROI: SAS Enterprise Miner typically involves higher upfront costs but provides substantial long-term ROI. Amazon SageMaker, with its pay-as-you-go pricing, allows cost-effective scaling and faster ROI realization. Its flexible pricing model supports rapid implementation and alignment with business needs.

To learn more, read our detailed Amazon SageMaker vs. SAS Enterprise Miner Report (Updated: December 2025).

Buyer's Guide

Amazon SageMaker vs. SAS Enterprise Miner

December 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

7.0

Number of Reviews

Ranking in other categories

AI Development Platforms (4th)

SAS Enterprise Miner

Ranking in Data Science Platforms

23rd

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

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 SAS Enterprise Miner is 1.6%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
Amazon SageMaker	4.6%
SAS Enterprise Miner	1.6%
Other	93.8%

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, 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.

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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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Quotes from Members

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

Pros

"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."

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

"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."

"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."

"The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc."

"We've had no problems with SageMaker's stability."

"The product aggregates everything we need to build and deploy machine learning models in one place."

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

More Amazon SageMaker pros

"Good data management and analytics."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"The most valuable feature is the decision tree creation."

"The solution is very good for data mining or any mining issues."

"he solution is scalable."

"I like the way the product visually shows the data pipeline."

More SAS Enterprise Miner pros

Cons

"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

"I would recommend having more walkthrough videos and articles beyond AWS Skill Builder."

"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."

"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."

"In general, improvements are needed on the performance side of the product's graphical user interface-related area since it consumes a lot of time for a user."

"The documentation must be made clearer and more user-friendly."

"AI is a new area and AWS needs to have an internship training program available."

More Amazon SageMaker cons

"The user interface of the solution needs improvement. It needs to be more visual."

"The solution is much more complex than other options."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"Technical support could be improved."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"Virtualization could be much better."

"The visualization of the models is not very attractive, so the graphics should be improved."

"The initial setup is challenging if doing it for the first time."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

"Amazon SageMaker is a very expensive product."

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

"The solution is relatively cheaper."

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

"SageMaker is worth the money for our use case."

"The pricing could be better, especially for querying. The per-query model feels expensive."

More Amazon SageMaker pricing and cost advice

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

"This solution is for large corporations because not everybody can afford it."

"The solution must improve its licensing models."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

10%

Manufacturing Company

University

Financial Services Firm

25%

Educational Organization

11%

Manufacturing Company

10%

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	11
Large Enterprise	17

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	4
Large Enterprise	7

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...

See all answers

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?

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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Product Reports

Buyer's Guide

Amazon SageMaker

January 2026

Download Amazon SageMaker product report

Buyer's Guide

Data Mining

January 2026

Download SAS Enterprise Miner product report

Also Known As

AWS SageMaker, SageMaker

Enterprise Miner

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)

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

SAS

Sample Customers

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

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Amazon SageMaker vs. SAS Enterprise Miner

December 2025

Free Report: Amazon SageMaker vs. SAS Enterprise Miner

Find out what your peers are saying about Amazon SageMaker vs. SAS Enterprise Miner and other solutions. Updated: December 2025.

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