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 6.9% mindshare in Data Science Platforms, compared to SAS’s 0.8% 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

5,661 Views
4,573 Comparison Views

91% willing to recommend

SAS Enterprise Miner

Read 13 SAS Enterprise Miner reviews

626 Views
475 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: April 2025).

Buyer's Guide

Amazon SageMaker vs. SAS Enterprise Miner

April 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 May 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 6.9%, down from 9.7% compared to the previous year. The mindshare of SAS Enterprise Miner is 0.8%, down from 0.9% 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 tool makes our ML model development a bit more efficient because everything is in one environment."

"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 solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."

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

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

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

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

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

More Amazon SageMaker pros

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

"Good data management and analytics."

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

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

"he solution is scalable."

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

"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."

More SAS Enterprise Miner pros

Cons

"The solution needs to be cheaper since it now charges per document for extraction."

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

"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."

"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 solution is complex to use."

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

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

"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."

More Amazon SageMaker cons

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

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

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

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

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

More SAS Enterprise Miner cons

Pricing and Cost Advice

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

"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."

"Databricks solution is less costly than Amazon SageMaker."

"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."

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

"I would rate the solution's price a ten out of ten since it is very high."

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

More Amazon SageMaker pricing and cost advice

"The solution must improve its licensing models."

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

"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

19%

Educational Organization

11%

Computer Software Company

11%

Manufacturing Company

Financial Services Firm

26%

University

12%

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?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

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

Comparisons

Databricks vs Amazon SageMaker

Compared 15% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 11% of the time

Google Vertex AI vs Amazon SageMaker

Compared 8% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

More Amazon SageMaker Competitors

SAS Visual Analytics vs SAS Enterprise Miner

Compared 29% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 23% of the time

KNIME vs SAS Enterprise Miner

Compared 23% of the time

Altair RapidMiner vs SAS Enterprise Miner

Compared 17% of the time

Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

Compared 9% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

Amazon SageMaker

May 2025

Download Amazon SageMaker product report

Buyer's Guide

Data Mining

April 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

April 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: April 2025.

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