Sold by: SAS
Deployed on AWS
New analytical developer canvas! Conduct exploratory data analysis to develop AI/ML models using SAS, Python or R. Quickly and easily innovate, experiment, iterate, and create powerful models. Learn More: Built for developers , SAS Viya Workbench is designed to create powerful advanced analytics using a variety of statistical and machine learning techniques. Use SAS, Python or R code in Visual Studio Code and Jupyter Notebook/JupyterLab to develop analytical and machine learning models quickly and easily with SAS, Python or R. Self-provisioning with minimal IT support needed. Choose compute power CPU/GPU to match your analytical workload. Access proven and powerful SAS analytical procedures, Python APIs and R Runtime. SAS Viya Workbench provides development and data science teams the ability to bring their own code using Visual Studio Code and Jupyter Notebook interfaces into a self-service data and compute environment - optimizing team productivity.
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Overview
SAS Viya Workbench is a developer canvas for experimentation and exploration. Viya Workbench allows developers and modelers to work in the language of their choice of SAS, Python or R. Using an intuitive and flexible interface, Viya Workbench offers two development environment options - Jupyter Notebook/JupyterLab and Visual Studio Code. Tap into powerful SAS analytical procedures (PROCs), native Python APIs, or R Runtime. Accelerate development of high-performance AI models. Additionally, access state-of-the-art, custom Python libraries - unique to Viya Workbench - that can significantly improve speed and performance with minimal changes to a developer's existing Python program. Viya Workbench is a flexible, scalable and efficient development environment that is on-demand, self-provisioning and self-terminating with minimal IT support. The dedicated analytical environment features customizable CPU/GPU compute power to match the needs of the project. Models and other results can be leveraged in various production environments, including SAS Viya, for data management, governance and operational deployment. Increase developer productivity with faster AI innovation. Work with modern, open source packages and cutting-edge cloud compute. Deliver fast results and manage costs. Leverage prebuilt, scalable infrastructures that allow you to focus on creating, innovating, iterating and testing your work. Improve efficiency, compute speed, results and ultimately, time to value.
Highlights
- Developer Canvas: Novice and advanced developers and data scientists can innovate, experiment, iterate, and create in a lightweight, scalable, cloud native environment that enables developers to rapidly build highly performant analytical models.
- Open Source Flexibility: Code in SAS, Python or R using web-based industry standard code editors Visual Studio Code & Jupyter Notebook. Leverage existing projects or develop from scratch using the latest powerful SAS Procedures (PROCS), Python APIs, and R Runtime.
- Efficient Compute Engine: Assign compute tiers to enable on demand, independent provisioning. Right-size cores, memory, and GPU compute power. Scale up or down to match analytical needs. On demand and self-terminating servers for optimal efficiency.
Details
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Delivery method
Delivery option
SAS Viya Workbench Dataplane Topology
Latest version
Operating system
AmazonLinux 2023.1.0
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
WorkbenchDataPlane | SAS Viya Workbench Data Plane | $0.00 |
WorkbenchUsers | SAS Viya Workbench Users | $0.01 |
Vendor refund policy
Refunds are not provided.
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
SAS Viya Workbench Dataplane Topology
CloudFormation template for provisioning a SAS Workbench DataPlane that adheres to customer information policies.
The AMI provisioned using this template adhere to the following customer information policies:
- Customer data collected: email address (CustomerAdminEmail) will be sent to SAS and used to contact the buyer in regards to the SAS Viya Workbench
The AMI provisions IAM policies to provision the necessary components to build and EKS Cluster along with Node pool groups. More details are found in the documentation.
Warning: This will create appropriate IAM roles for proper deployment of SAS Viya Workbench in EKS Cluster.
CloudFormation Template (CFT)
AWS CloudFormation templates are JSON or YAML-formatted text files that simplify provisioning and management on AWS. The templates describe the service or application architecture you want to deploy, and AWS CloudFormation uses those templates to provision and configure the required services (such as Amazon EC2 instances or Amazon RDS DB instances). The deployed application and associated resources are called a "stack."
Version release notes
Updated CFT and AMI to add encryption to EBS volumes by default
Additional details
Usage instructions
To connect to the operating system, use SSH and the username ec2-user.
Resources
Vendor resources
Support
Vendor support
Move Your Business Forward, Faster! -Get SAS Viya Workbench up and running with minimal interruption. -Evolve your skills with online resources. -Quickly benefit from hot fixes and product updates. -Get well-informed answers from several different disciplines, including research and development, consulting services and more. -Product documentation -Online Support -Telephone Support -SAS Communities Support -Free and paid training opportunities
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By SAS
By Domino Data Lab
By Teradata
Top
10
In Analytics, Data Analytics, ML Solutions
Top
10
In Business Intelligence & Advanced Analytics, ML Solutions, Data Analytics
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Multi-Language Development Support
Support for SAS, Python, and R programming languages with access to SAS analytical procedures (PROCs), native Python APIs, and R Runtime.
Integrated Development Environments
Web-based code editors including Visual Studio Code and Jupyter Notebook/JupyterLab for analytical model development.
Customizable Compute Resources
On-demand provisioning with configurable CPU and GPU compute power that can be scaled up or down to match analytical workload requirements.
Custom Python Libraries
State-of-the-art custom Python libraries optimized for performance improvement with minimal modifications to existing Python programs.
Self-Service Infrastructure
Self-provisioning and self-terminating cloud-native environment with minimal IT support requirements for development and data science teams.
Self-Service Infrastructure Access
One-click, governed access to data, tools, and compute resources through a self-service portal with support for open-source tools including Jupyter, RStudio, SAS, Anaconda, MATLAB, and distributed compute frameworks like Spark, Ray, Dask, and MPI.
Centralized Knowledge Management
Central hub for AI operations and knowledge across the enterprise enabling reproducibility, reusability, and cross-functional collaboration with audit-ready platform capabilities.
Integrated MLOps Workflows
End-to-end model development, deployment, and monitoring capabilities within a unified platform with support for preferred tools and languages, including seamless integration with Amazon SageMaker.
Multi-Cloud and Hybrid Deployment
Support for deployment across public cloud, hybrid, and multi-cloud environments through Domino Nexus, enabling workload execution across any compute cluster in any cloud, region, or on-premises infrastructure.
Model Governance and Compliance
Turnkey model governance, monitoring, and remediation with robust controls for compliance, reproducibility tracking, and audit-ready processes designed for regulatory requirements including GxP processes.
In-Engine Analytics Capabilities
Advanced in-engine analytics powered by ClearScape Analytics with high-performance compute and massive parallel processing capabilities
Open Table Format Support
Support for Apache Iceberg and Delta Lake open table formats with simultaneous connection to multiple open catalogs enabling cross-read, cross-write, and cross-query operations
Multi-Cloud Data Access
Access to data lakes across multi-cloud and multi-data-lake environments with compatibility for open file formats including Parquet and CSV
Python Integration
Integration with Python for calling analytics functions, executing Python code, and importing Python models directly into the engine with Jupyter Notebook access
Seamless Production Transition
Ability to transition and operationalize prototypes from development environment into VantageCloud production environment without data movement or infrastructure reconfiguration
Standard contract
No
No
No
Customer reviews
Khushal Jdai
Modern analytics has transformed large data into faster insights and streamlined reporting
Reviewed on Mar 21, 2026
Review from a verified AWS customer
What is our primary use case?
My main use cases are data analytics, reporting, and data transformation. It helps in handling large data sets efficiently using CAS, which is an in-memory processing engine. My primary use case is to analyze large-scale data and generate actionable insights.
In a recent project, I used SAS Viya Platform to analyze sales performance data. I first performed data preparation and transformation to clean and structure raw data from multiple sources. Then I leveraged CAS for fast in-memory processing of large data sets. After that, I built an interactive dashboard in Visual Analytics to track KPIs such as revenue, growth, and regional performance.
On a day-to-day basis, I use SAS Viya Platform mainly for data preparation, analysis, and reporting. I regularly work on data cleaning and transformation to make data sets analysis-ready. I also monitor data refreshes and validate data accuracy to ensure reliable reporting. Based on that, I update dashboards or create new reports in Visual Analytics.
What is most valuable?
The best features SAS Viya Platform offers are that it is fully managed by SAS, so no infrastructure setup is needed. It is a cloud-native SaaS architecture. It also provides high-performance processing with CAS, which is an in-memory distributed engine for handling larger data sets. SAS Viya Platform gives me an end-to-end analytics platform where I can perform modeling, visualization, and deployment. Additionally, it offers powerful data visualization capabilities.
A hidden gem I find really valuable in SAS Viya Platform is the in-memory architecture of CAS combined with parallel processing. It is not just fast, but it allows handling larger data sets seamlessly without performance bottlenecks. Additionally, new features and fixes are rolled out without any downtime or manual efforts, which is the main advantage of this.
SAS Viya Platform has significantly improved my organization's data processing and reporting efficiency. Previously, handling larger data sets used to take more time, but with CAS in-memory processing, performance has improved considerably. Overall, it has enabled faster and more data-driven decision-making. Due to parallel and in-memory computing, data processing time has been reduced significantly for my organization. The SaaS model has also reduced infrastructure and maintenance overhead, allowing us to focus more on delivering business value. SAS Viya Platform has improved the speed, scalability, and accessibility of data, leading to more efficient and informed decision-making.
Using SAS Viya Platform, I saw approximately a thirty to forty percent reduction in data processing time due to CAS in-memory computing. I also reduced manual reporting efforts by approximately forty to fifty percent through automation and self-service dashboards, which definitely saved resources for my organization. For example, the weekly sales report that previously took three or four hours to prepare manually is now available in less than an hour through automated dashboards. While extracting a direct revenue impact is difficult to quantify, the platform has clearly improved efficiency, speed, and decision-making quality.
What needs improvement?
There are some areas of improvement I would mention regarding SAS Viya Platform. New users may find it complex initially, as its learning curve can be steep. Understanding CAS and different components is very challenging for a new user. The cost is also quite high; SAS Viya Platform via SaaS can be expensive compared to some open-source or other cloud alternatives.
There are also some limitations in Visual Analytics. While it is easy to use, it could be more flexible compared to Power BI or Tableau. These are the main improvement areas where SAS Viya Platform should focus.
I would add some additional pointers about needed improvements in SAS Viya Platform. Regarding customer support, it is good, but the response time for complex issues can sometimes be slower than expected. The documentation and learning resources are not very beginner-friendly, making it challenging for beginners to navigate.
Regarding integration, it could be smoother with Databricks , Snowflake , and Power BI, but it is more complex than it should be. Since updates are automatic, users are sometimes not fully aware of changes or new features that are being updated, as compared to Power BI, which publishes updates on its website. SAS Viya Platform should work on these aspects.
For how long have I used the solution?
I have been using SAS Viya Platform for the past two years.
What other advice do I have?
I advise others looking into using SAS Viya Platform to leverage the CAS engine effectively to get the best performance for larger data sets. It is important to have well-defined use cases before adopting SAS Viya Platform, whether it is reporting, advanced analytics, or machine learning. You should also invest time in learning the platform as there are initial learning curves involved. Proper planning of data architecture and integration with existing systems is crucial. Monitoring cost and usage is also important, especially with SAS Viya Platform. SAS Viya Platform is a very easy-to-use platform. I would rate this product an 8 overall.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
reviewer2783847
Integrated analytics have streamlined healthcare risk adjustment and improved visit targeting
Reviewed on Dec 02, 2025
Review from a verified AWS customer
What is our primary use case?
My main use case for SAS Viya Platform is analytics on risk adjustment in the healthcare field.
One of the specific examples of how I use SAS Viya Platform for risk adjustment analytics in healthcare is to determine the population of members that are more likely to not get an annual visit with their primary care physician. That is one of the use cases and how we follow up with them. This is also used in a predictive analytics sense where we need to provide and generate a list of members for whom we have to chase and get an EMR or a chart. So mostly in the predictive analytics area.
What is most valuable?
The best features that SAS Viya Platform offers are the easy visualization of the results, which stands out for me, and also the ease of using the AI agents to describe the problem and come up with the solution.
The visualization and AI agent features of SAS Viya Platform help me in my day-to-day work. For example, one aspect of the visualization is how by looking at the graphs, you can determine which area, such as the plan area in the healthcare insurance field, we need to focus on and where we are falling short. It is easily visualized, mostly for the marketing team in the provider area that needs to concentrate there.
SAS Viya Platform has positively impacted my organization. Previously, the team had SAS developers and the data was fed into a different visualization tool such as Tableau or Power BI. This eliminates the need for that.
Eliminating the need for separate visualization tools has greatly affected my team's workflow because it is just one integrated tool, one integrated platform. You do not have to worry about the connections to Tableau, generating the output, and if there is an issue with a live connection on Tableau, then the visualization does not show up, and that is the end of it. We would need to wait for a resolution from another team, and this eliminates the need for that.
What needs improvement?
I cannot think of any improvements for SAS Viya Platform from the top of my head, although users might have suggestions.
I would add that some users need more training in SAS and SAS Viya Platform. An AI assist, such as a live assist, would be helpful for them.
For how long have I used the solution?
I have been using SAS Viya Platform for three years.
What do I think about the stability of the solution?
SAS Viya Platform is stable.
What do I think about the scalability of the solution?
The scalability of SAS Viya Platform is pretty good. We have seen that it has been scalable, especially because with each year, there is an increasing number of members in the healthcare insurance, and with the member increase, you are also going to see the claim population increase. We have not had a problem, and it is because it is on the cloud, it scales quite well.
How are customer service and support?
Apart from the initial setup, we have not used customer support a lot, but it was pretty good.
Which solution did I use previously and why did I switch?
I previously used a different solution before SAS Viya Platform. It was legacy systems, SAS on Unix, and then Tableau.
How was the initial setup?
My experience with pricing, setup cost, and licensing for SAS Viya Platform was smooth. I did not have any hiccups, and I do not have a say on the pricing.
What was our ROI?
I have seen a return on investment with SAS Viya Platform in the form of money saved, as this is scalable and on the cloud, whereas previously we had to pay for space and on-premises servers.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing for SAS Viya Platform was smooth. I did not have any hiccups, and I do not have a say on the pricing.
Which other solutions did I evaluate?
Before choosing SAS Viya Platform, I did evaluate other options, but it was not a total solution. It involved a process where part of the development had to be done on AWS , PySpark coding, and then the results were imported into one of the visualization tools such as Quicksight or Tableau.
What other advice do I have?
I would advise others looking into using SAS Viya Platform to go ahead if their budget allows. I have rated this product an eight out of ten.