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 8.0, while SAS is ranked #18 with an average rating of 9.0. Amazon Web Services (AWS) holds a 6.2% mindshare in Data Science Platforms, compared to SAS’s 0.9% 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 37 Amazon SageMaker reviews

7,896 Views
4,738 Comparison Views

91% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

842 Views
598 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: June 2025).

Buyer's Guide

Amazon SageMaker vs. SAS Enterprise Miner

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

3rd

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Development Platforms (5th)

SAS Enterprise Miner

Ranking in Data Science Platforms

18th

Average Rating

7.6

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Mining (7th)

Mindshare comparison

As of July 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.2%, down from 9.3% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.9%, up from 0.8% 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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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

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

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

"The technical support from AWS is excellent."

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

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

"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."

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

"It's user-friendly for business teams as they can understand many aspects through the AWS interface."

More Amazon SageMaker pros

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

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

"he solution is scalable."

"The technical support is very good."

"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."

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

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

"Good data management and analytics."

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."

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

"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."

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

"There is room for improvement in the collaboration with serverless architecture, particularly integration with AWS Lambda."

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

"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."

More Amazon SageMaker cons

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

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

"The ease of use can be improved. When you are new it seems a bit complex."

"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."

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

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

"Virtualization could be much better."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The product is expensive."

"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."

"Databricks solution is less costly than Amazon SageMaker."

"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."

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

"The solution is relatively cheaper."

"Amazon SageMaker is a very expensive product."

"The pricing is comparable."

More Amazon SageMaker pricing and cost advice

"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."

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

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

12%

Manufacturing Company

Educational Organization

Financial Services Firm

27%

University

10%

Educational Organization

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

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...

See all answers

What do you like most about SAS Enterprise Miner?

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

See all answers

What is your experience regarding pricing and costs for SAS Enterprise Miner?

The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a subset of the functionality available according to our license. I rate the pric...

See all answers

What needs improvement with SAS Enterprise Miner?

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

See all answers

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Compared 9% of the time

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Compared 25% of the time

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Compared 21% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 19% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 19% of the time

TIBCO Data Science vs SAS Enterprise Miner

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Product Reports

Buyer's Guide

Amazon SageMaker

July 2025

Download Amazon SageMaker product report

Buyer's Guide

Data Mining

June 2025

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

June 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: June 2025.

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