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Amazon SageMaker vs SAS Visual Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.3
Amazon SageMaker delivers high ROI by reducing costs and time, often providing returns multiple times the initial investment.
Sentiment score
6.3
Organizations saw varied ROI from SAS Visual Analytics, noting improved efficiency and financial tracking despite initial cost challenges.
The return on investment varies by use case and offers significant value in revenue increases and cost saving capabilities, especially in real time fraud detection and targeted advertisements.
The enterprise subscription offers more benefits, ensuring valuable outcomes.
 

Customer Service

Sentiment score
7.2
Amazon SageMaker support is generally praised, but service quality varies; premium customers receive better, more responsive assistance.
Sentiment score
6.8
SAS Visual Analytics customer service is mixed, with praise for technical support but noted gaps in business needs and regional availability.
The technical support from AWS is excellent.
The response time is generally swift, usually within seven to eight hours.
The support is very good with well-trained engineers.
They provide callbacks to ensure clarity and resolution of any queries.
 

Scalability Issues

Sentiment score
7.6
Amazon SageMaker offers scalability and adaptability across enterprises, but GPU limitations and user skills impact its overall efficiency.
Sentiment score
7.8
SAS Visual Analytics effectively scales for large datasets and users, though high resource demands and expenses may concern some.
It works very well with large data sets from one terabyte to fifty terabytes.
The availability of GPU instances can be a challenge, requiring proper planning.
Amazon SageMaker is scalable and works well from an infrastructure perspective.
 

Stability Issues

Sentiment score
7.8
Amazon SageMaker is stable with high reliability, especially when properly configured, and minor glitches do not significantly impact performance.
Sentiment score
7.1
SAS Visual Analytics is generally reliable but can face performance issues with large data, often due to user practices.
There are issues, but they are easily detectable and fixable, with smooth error handling.
I rate the stability of Amazon SageMaker between seven and eight.
SAS Visual Analytics is stable and manages data effectively without crashing.
 

Room For Improvement

Users seek better pricing, interface, integration, documentation, AI, dataset support, security, serverless options, and AWS collaboration.
SAS Visual Analytics is complex and costly, with challenges in integration, performance, user-friendliness, and external language support.
Both SageMaker and Lambda are powerful tools, and combining their capabilities could be beneficial.
This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background.
Integration of the latest machine learning models like the new Amazon LLM models could enhance its capabilities.
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI.
 

Setup Cost

Amazon SageMaker offers flexible, competitive pricing but can be costly, with value varying by user, plus available discounts.
SAS Visual Analytics is costly for small enterprises, but offers strong analytics and simplicity, though consulting and scaling add expenses.
The cost for small to medium instances is not very high.
The pricing can be up to eight or nine out of ten, making it more expensive than some cloud alternatives yet more economical than on-premises setups.
For a single user, prices might be high yet could be cheaper for user-managed services compared to AWS-managed services.
 

Valuable Features

Amazon SageMaker offers comprehensive tools for end-to-end machine learning, including model deployment, scalability, and user-friendly features.
SAS Visual Analytics excels in data visualization, advanced analytics, and user-friendly interface with rapid processing and seamless integration.
SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project.
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.
These features facilitate rapid development and deployment of AI applications.
The ability to query information from our Excel data into SAS to view specific data is invaluable.
 

Categories and Ranking

Amazon SageMaker
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
37
Ranking in other categories
Data Science Platforms (3rd), AI Development Platforms (5th)
SAS Visual Analytics
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
40
Ranking in other categories
Data Visualization (7th)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Amazon SageMaker is designed for Data Science Platforms and holds a mindshare of 6.9%, down 9.7% compared to last year.
SAS Visual Analytics, on the other hand, focuses on Data Visualization, holds 4.2% mindshare, down 6.0% since last year.
Data Science Platforms
Data Visualization
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
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.
Renato Vazamin - PeerSpot reviewer
Single environment for multiple phases saves us time, and has good visualizations
We had that solution installed previously in another solution, Selvaya, but I don't think we used it at the time. We are now using SAS Detect Investigation as a complementary solution, in which we have part of the process, use a gene, SAS collects information and identifies some business situations, and the business guys use Visual Analytics to explore the results of the process. We previously used the FICO platform, but we switched because FICO's pricing was not scalable. Bringing more data or workloads to the platform required a significant investment in order to scale. We needed to change because we have a lot of data to process every day. FICO was also a little more complicated than SAS Visual Analytics.
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
11%
Educational Organization
11%
Manufacturing Company
8%
Financial Services Firm
21%
Government
12%
Computer Software Company
10%
University
8%
 

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...
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?
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...
What do you like most about SAS Visual Analytics?
The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps w...
What is your experience regarding pricing and costs for SAS Visual Analytics?
It's about an average of five. It's easy to scale, but it comes with cost.
What needs improvement with SAS Visual Analytics?
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI. It may be that our current subscription does not include AI-enabled features, but I wo...
 

Also Known As

AWS SageMaker, SageMaker
SAS BI
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.
Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: May 2025.
851,823 professionals have used our research since 2012.