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 #3 with an average rating of 8.3, while SAS is ranked #23. Amazon Web Services (AWS) holds a 3.6% mindshare in Data Science Platforms, compared to SAS’s 1.8% mindshare. Additionally, 92% 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 39 Amazon SageMaker reviews

6,333 Views
3,673 Comparison Views

92% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,532 Views
1,195 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: March 2026).

Buyer's Guide

Amazon SageMaker vs. SAS Enterprise Miner

March 2026

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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

3rd

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 April 2026, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 3.6%, down from 7.3% compared to the previous year. The mindshare of SAS Enterprise Miner is 1.8%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Mindshare Distribution
Product	Mindshare (%)
Amazon SageMaker	3.6%
SAS Enterprise Miner	1.8%
Other	94.6%

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

"They offer insights into everyone making calls in my organization."

"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."

"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."

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

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

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

"The tool makes our ML model development a bit more efficient because everything is in one environment."

"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."

More Amazon SageMaker pros

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

"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, and the results and the ensembles are fantastic."

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

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

"The solution is able to handle quite large amounts of data beautifully."

"Performance is excellent."

"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."

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

More SAS Enterprise Miner pros

Cons

"From the cost point of view, it's relatively on the higher side."

"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."

"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."

"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."

"The main challenge with Amazon SageMaker is the integrations."

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

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

"Comparatively, GCP offers very low cost when compared to Amazon SageMaker. People are moving from Amazon SageMaker to GCP because of the cost constraints."

More Amazon SageMaker cons

"The preparation of both the mining and modeling process could be improved. The solution requires data and will reflect data, but the preparation of the data is not useful for end-users; we ended up having to do the preparation in another tool."

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

"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."

"The solution is quite expensive. The pricing is too high."

"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."

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

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

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

More SAS Enterprise Miner cons

Pricing and Cost Advice

"Databricks solution is less costly than Amazon SageMaker."

"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 tool's pricing is reasonable."

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

"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."

"The pricing is comparable."

"The solution is relatively cheaper."

More Amazon SageMaker pricing and cost advice

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

"The solution must improve its licensing models."

"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."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

University

Financial Services Firm

19%

Construction Company

12%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	11
Large Enterprise	18

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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Comparisons

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Compared 9% of the time

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Compared 5% of the time

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Compared 12% of the time

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Compared 8% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 7% of the time

SAS Analytics vs SAS Enterprise Miner

Compared 5% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 5% of the time

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Product Reports

Buyer's Guide

Amazon SageMaker

April 2026

Download Amazon SageMaker product report

Buyer's Guide

Data Mining

March 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

March 2026

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: March 2026.

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