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 8.2, while SAS is ranked #24. Amazon Web Services (AWS) holds a 4.0% mindshare in Data Science Platforms, compared to SAS’s 1.7% 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

6,234 Views
3,616 Comparison Views

92% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

1,291 Views
1,007 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

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

24th

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 4.0%, down from 7.5% compared to the previous year. The mindshare of SAS Enterprise Miner is 1.7%, 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	4.0%
SAS Enterprise Miner	1.7%
Other	94.3%

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

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

"I have seen a return on investment, probably a factor of four or five."

"The technical support from AWS is excellent."

"The solution is easy to scale...The documentation and online community support have been sufficient for us so far."

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

"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."

"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 these models, making accessing them convenient as needed."

"The evolution from SageMaker Classic to SageMaker Studio, particularly the UI part of Studio, is commendable."

More Amazon SageMaker pros

"Good data management and analytics."

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

"Performance is excellent."

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

"he solution is scalable."

"The technical support is very good."

"It enables statistical modeling of data using Base SAS (another product from the same vendor) as the backbone."

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

More SAS Enterprise Miner pros

Cons

"For any cloud provider, the cost has to be substantially reduced, especially in the case of Amazon SageMaker, which is extremely expensive for huge workloads."

"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."

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

"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."

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."

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

"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 product must provide better documentation."

More Amazon SageMaker cons

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

"The license is really expensive. This solution is for large corporations because not everybody can afford it."

"Virtualization could be much better."

"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 much more complex than other options."

"The product must provide better integration with cloud-native technologies."

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

More SAS Enterprise Miner cons

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."

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

"The product is expensive."

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

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

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

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

"Databricks solution is less costly than Amazon SageMaker."

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%

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...

See all answers

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.

See all answers

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Comparisons

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Compared 9% of the time

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Compared 7% of the time

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Compared 6% of the time

Dataiku vs Amazon SageMaker

Compared 5% of the time

DataRobot vs Amazon SageMaker

Compared 5% of the time

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KNIME Business Hub vs SAS Enterprise Miner

Compared 13% of the time

Azure Data Lake Analytics vs SAS Enterprise Miner

Compared 8% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 6% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 5% of the time

SAS Visual Analytics 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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