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Monte Carlo vs SAS Viya Platform 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
6.9
Monte Carlo accelerates data issue detection by 60%-70% and reduces downtime by 40%-50%, saving 1,200 hours annually.
Sentiment score
4.4
SAS Viya Platform enhances ROI with AI, automation, cost savings, cloud scalability, data visualization, and efficiency improvements.
It definitely reduces resource hours needed for work, lessening the effort required significantly compared to when Monte Carlo is not in place.
Data Engineer & Management & Governance Senior Analyst at a tech vendor with 10,001+ employees
Monte Carlo has solved the challenge of monitoring ingestion health at scale.
Data Analyst at Teshama Group
Monte Carlo saves me roughly 30% to 40% of my time in doing verifications or data quality checks.
Enterprise Network Architect at Concordia University-Wisconsin
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.
Director, Lead, Ri Technical Solutions at a insurance company with 10,001+ employees
We generate revenue from the data visualization options, which is a very important key aspect for return of investment.
Biostatistician at Lambda Therapeutic Research Ltd.
The relevant metrics definitely show time saved because it is able to crunch 50 to 60,000 rows of numbers in a matter of five to ten minutes, which is a huge improvement.
Computer Instructor at Carleton University
 

Customer Service

Sentiment score
6.2
Monte Carlo's customer service is highly rated for providing responsive and efficient support through a team and AI platform.
Sentiment score
5.1
SAS Viya Platform offers highly rated, responsive customer service, with excellent support during migrations, despite limited community assistance.
When I requested help regarding the deletion of monitors, I received a very good and quick response.
Data Engineer & Management & Governance Senior Analyst at a tech vendor with 10,001+ employees
Monte Carlo's customer support team responds very fast.
Staff Data Engineer at a media company with 5,001-10,000 employees
My experiences reaching out to them show that they were very quick to help and very professional.
Data Analyst at Teshama Group
I would rate customer support for SAS Viya Platform a 10 out of 10.
Biostatistician at Lambda Therapeutic Research Ltd.
we have received help whenever we have asked, and their response time is quite fast
Senior Data Analyst at a government with 201-500 employees
we got the solution on time
Technical Architect at a tech vendor with 10,001+ employees
 

Scalability Issues

Sentiment score
7.4
Monte Carlo scales effectively, accommodating increased data demands and providing flexibility for organizations experiencing growth and expanding data volumes.
Sentiment score
6.0
SAS Viya Platform is highly scalable, efficiently managing large data and growing user demands without performance issues in the cloud.
Monte Carlo's scalability is impressive.
Data Engineer & Management & Governance Senior Analyst at a tech vendor with 10,001+ employees
As our company's business grows and the data volume increases, Monte Carlo scales very well.
Staff Data Engineer at a media company with 5,001-10,000 employees
Monte Carlo is robust and scalable for our data needs.
Senior Data & Platforms Engineer at PepsiCo
We have not had a problem, and it is because it is on the cloud, it scales quite well.
Director, Lead, Ri Technical Solutions at a insurance company with 10,001+ employees
SAS Viya Platform is quite scalable and can handle large data volumes.
Senior Data Analyst at a government with 201-500 employees
SAS Viya Platform's scalability is great; it can be scaled throughout the project, even company-wide.
Technical Architect at a tech vendor with 10,001+ employees
 

Stability Issues

Sentiment score
8.7
Users praise Monte Carlo for its stable and reliable performance, noting its consistent uptime and absence of crashes.
Sentiment score
7.6
The SAS Viya Platform is mostly stable and scalable, though some users noted occasional lags and downtime resolved by support.
I did not see any issues with respect to stability.
Principal Data Engineer at Teradata Corporation
SAS Viya Platform is good, scalable, and stable.
Data & BI Architect at a outsourcing company with 5,001-10,000 employees
In my experience, SAS Viya Platform is stable and perfect.
Computer Instructor at Carleton University
 

Room For Improvement

Monte Carlo struggles with AI accuracy, user experience, anomaly detection, UI, monitor deletion, database features, and pricing competitiveness.
SAS Viya Platform needs interface simplification, better integration, enhanced reporting, and improved training resources for streamlined user experience.
Artificial intelligence can access multiple systems underneath Monte Carlo, such as any kind of database or any kind of real-time source systems.
Principal Data Engineer at Teradata Corporation
Monte Carlo has just updated the UI. The previous one was user-friendly, and now they have added AI-related elements in the current UI, which is good.
Data Engineer & Management & Governance Senior Analyst at a tech vendor with 10,001+ employees
They need to find their way back, establish a product roadmap, and have real engineers work on improvements rather than heavily push AI down users' throats.
Senior Data & Platforms Engineer at PepsiCo
Two main improvements would transform this into a great tool: improving the UI and calculation capabilities, and merging AI capabilities.
Data & BI Architect at a outsourcing company with 5,001-10,000 employees
The cost is also quite high; SAS Viya Platform via SaaS can be expensive compared to some open-source or other cloud alternatives.
Assistant Manager Data Analytics (WFM) at Johari Digital Healthcare Limited
In comparison, other packages I have used are more complete and less divided; SAS is quite divided, particularly with quality control, which used to be included, but now requires separate packages for control charts and so on.
Senior Data Analyst at a government with 201-500 employees
 

Setup Cost

Monte Carlo offers reasonable pricing for enterprise observability, with manageable setup costs and adaptable licensing for different organization sizes.
Enterprise users find SAS Viya cost-effective, though some perceive it as expensive; comparisons with Tableau or Power BI are rare.
I find it highly affordable for any organization sizes.
Data Analyst at Teshama Group
I did check with Reddit and they indicated that SAS Viya Platform is a pretty expensive program.
Computer Instructor at Carleton University
My experience with pricing, setup cost, and licensing is very positive, as the pricing is good and efficient for my organization.
Biostatistician at Lambda Therapeutic Research Ltd.
My experience with pricing, setup cost, and licensing for SAS Viya Platform was smooth.
Director, Lead, Ri Technical Solutions at a insurance company with 10,001+ employees
 

Valuable Features

Monte Carlo enhances data reliability through AI-driven alerts, anomaly detection, and integration, reducing manual effort and improving decision-making.
SAS Viya Platform enhances data processing with AI features, cloud-native architecture, and integration, supporting efficient, no-code decision-making.
Monte Carlo has accelerated the development process and has reduced the testing time significantly.
AI Machine Learning Engineer at a tech vendor with 10,001+ employees
The system does not send false alerts.
Principal Data Engineer at Teradata Corporation
Monte Carlo has positively impacted my organization by significantly reducing manual tasks.
Data Engineer & Management & Governance Senior Analyst at a tech vendor with 10,001+ employees
SAS Viya Platform has improved the speed, scalability, and accessibility of data, leading to more efficient and informed decision-making.
Assistant Manager Data Analytics (WFM) at Johari Digital Healthcare Limited
SAS Viya Platform has positively impacted my organization by saving time compared to when we were using SAS 9.4.
Saa S Developer at XpertDox
The speed and documentation of SAS Viya Platform helped me in my coursework because we were having very intense analyses done and we needed to submit a lot of assignments and analyses as quickly as possible.
Computer Instructor at Carleton University
 

Categories and Ranking

Monte Carlo
Ranking in Data Quality
23rd
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
8
Ranking in other categories
Data Observability (1st)
SAS Viya Platform
Ranking in Data Quality
8th
Average Rating
7.8
Reviews Sentiment
5.2
Number of Reviews
9
Ranking in other categories
Data Integration (27th), Data Governance (18th), Data Management Platforms (DMP) (8th)
 

Mindshare comparison

As of June 2026, in the Data Quality category, the mindshare of Monte Carlo is 1.4%, up from 1.2% compared to the previous year. The mindshare of SAS Viya Platform is 1.3%. It is calculated based on PeerSpot user engagement data.
Data Quality Mindshare Distribution
ProductMindshare (%)
SAS Viya Platform1.3%
Monte Carlo1.4%
Other97.3%
Data Quality
 

Featured Reviews

KB
Senior Data & Platforms Engineer at PepsiCo
Improved data health and incident reduction have revealed issues while AI direction still needs work
Monte Carlo needs to stop their reliance on AI, as it is not going well and is degrading the entire product. They need to find their way back, establish a product roadmap, and have real engineers work on improvements rather than heavily push AI down users' throats. They need to stop relying on AI as heavily as they have been doing, as this has really degraded the user experience. The overall direction they are taking with AI needs to be examined, as at some point it seems they have simply stopped making any improvements. We have not used Monte Carlo's AI capabilities significantly. We primarily use it for investigating alerts from time to time. However, we do not use it extensively, so I do not think it is fair to comment comprehensively on it. Their incident tracking and incident debugging bot is useful for new analysts who are starting onboard. It helps them debug incidents, get a clearer picture, and achieve a clear head start to reach the root of the problem faster. Regarding accuracy and reliability, I would rate it at eighty to eighty-five percent. Given the current inherent non-reliability of AI models, every single thing that Monte Carlo says needs to be validated.
KK
Assistant Manager Data Analytics (WFM) at Johari Digital Healthcare Limited
Modern analytics has transformed large data into faster insights and streamlined reporting
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.
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Top Industries

By visitors reading reviews
Financial Services Firm
10%
Computer Software Company
8%
Construction Company
7%
Retailer
7%
Construction Company
26%
Manufacturing Company
14%
Healthcare Company
10%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise9
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise9
Large Enterprise7
 

Questions from the Community

What is your experience regarding pricing and costs for Monte Carlo?
My experience with pricing, setup costs, and licensing is limited as that falls under the management team's responsibility.
What needs improvement with Monte Carlo?
One way Monte Carlo can be improved is when rules are breached, it sends an email containing alerts. However, if I want to analyze a particular alert deeper, I have to click on the alert link and f...
What is your primary use case for Monte Carlo?
Monte Carlo's main use case is setting rules to test the quality of data coming from the source side. For example, a rule can be set up for null checks in a particular column of source tables. If a...
What is your experience regarding pricing and costs for SAS Viya Platform?
I am not much aware of the pricing, setup cost, and licensing of SAS Viya Platform because that was handled by the administrator. However, I do not think it is too costly to use. I never did a comp...
What needs improvement with SAS Viya Platform?
One thing I expect more from SAS Viya Platform, specifically on the report side, is how the calculations work. It is not that strong in that sense. It was very difficult to build the required calcu...
What is your primary use case for SAS Viya Platform?
I have used SAS Viya Platform for almost three years in various ways, including preparing data, using it, generating extracts, and sending them through email to users. We also built an internal das...
 

Overview

Find out what your peers are saying about Monte Carlo vs. SAS Viya Platform and other solutions. Updated: June 2026.
902,270 professionals have used our research since 2012.