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Amazon SageMaker vs SAS Enterprise Miner comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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
39
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
13
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
ProductMindshare (%)
Amazon SageMaker3.6%
SAS Enterprise Miner1.8%
Other94.6%
Data Science Platforms
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
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.
reviewer1352853 - PeerSpot reviewer
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…

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."
"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."
"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."
"I have seen a return on investment, probably a factor of four or five."
"The support is very good with well-trained engineers whose training curriculum is rigorous."
"Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker."
"The deployment is very good, where you only need to press a few buttons."
"The most valuable feature of Amazon SageMaker for me is the model deployment service."
"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 found the ease of use of the solution the most valuable."
"SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help."
"The data processing of the solution is very good, easy to use, both for enterprise and personal use."
"The setup is straightforward. Deployment doesn't take more than 30 minutes."
"he solution is scalable."
"I like the way the product visually shows the data pipeline."
 

Cons

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"Lacking in some machine learning pipelines."
"The documentation must be made clearer and more user-friendly."
"The solution requires a lot of data to train the model."
"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."
"AI is a new area and AWS needs to have an internship training program available."
"One area for improvement is the pricing, which can be quite high."
"The main challenge with Amazon SageMaker is the integrations."
"The user interface of the solution needs improvement. It needs to be more visual."
"The solution is much more complex than other options."
"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 ease of use can be improved. When you are new it seems a bit complex."
"Virtualization could be much better."
"The solution is quite expensive. The pricing is too high."
"Price of the product"
"Technical support could be improved."
 

Pricing and Cost Advice

"The tool's pricing is reasonable."
"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."
"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."
"The support costs are 10% of the Amazon fees and it comes by default."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"There is no license required for the solution since you can use it on demand."
"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."
"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."
"The solution must improve its licensing models."
"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
18%
Manufacturing Company
9%
Computer Software Company
8%
University
5%
Financial Services Firm
19%
Construction Company
12%
Educational Organization
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise11
Large Enterprise18
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise4
Large Enterprise7
 

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...
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...
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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Also Known As

AWS SageMaker, SageMaker
Enterprise Miner
 

Overview

 

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
Find out what your peers are saying about Amazon SageMaker vs. SAS Enterprise Miner and other solutions. Updated: April 2026.
887,041 professionals have used our research since 2012.