No more typing reviews! Try our Samantha, our new voice AI agent.

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

"Allows you to create API endpoints."
"We were able to use the product to automate processes."
"SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project."
"One of the most valuable features of Amazon SageMaker for me is the one-touch deployment, which simplifies the process greatly."
"The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework."
"The tangible benefits we have observed from using Amazon SageMaker include improved time to insight and generally the common stack that is easier to support over time."
"The various integration options available in Amazon SageMaker, such as Firehose for connecting to data pipelines, are simple to use."
"The few projects we have done have been promising."
"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."
"Performance is excellent."
"The most valuable feature is the decision tree creation."
"It enables statistical modeling of data using Base SAS (another product from the same vendor) as the backbone."
"SAS internal support is very qualified and if we have any issues, we contact them and trust that they can help."
"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 setup is straightforward. Deployment doesn't take more than 30 minutes."
"Technical support has been good, and when I called them at the start of using the product with some issues they were very helpful."
 

Cons

"One area for improvement is the pricing, which can be quite high."
"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."
"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."
"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."
"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."
"I had to create custom templates for labeling multi-data sets, such as text and images, which was time-consuming."
"AI is a new area and AWS needs to have an internship training program available."
"The main challenge with Amazon SageMaker is the integrations."
"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 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 initial setup is challenging if doing it for the first time."
"Price of the product"
"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 much more complex than other options."
"Plus it is prohibitively expensive and is not available with perpetual licensing."
 

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."
"There is no license required for the solution since you can use it on demand."
"Databricks solution is less costly than Amazon SageMaker."
"You don't pay for Sagemaker. You only pay for the compute instances in your storage."
"The solution is relatively cheaper."
"I would rate the solution's price a ten out of ten since it is very high."
"The pricing is comparable."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"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."
report
Use our free recommendation engine to learn which Data Science Platforms solutions are best for your needs.
886,174 professionals have used our research since 2012.
 

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
9%
 

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.
Ask a question
Earn 20 points
 

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: March 2026.
886,174 professionals have used our research since 2012.