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Azure Data Factory vs SAS Data Integration Server comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 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

Azure Data Factory
Ranking in Data Integration
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (7th)
SAS Data Integration Server
Ranking in Data Integration
40th
Average Rating
7.2
Reviews Sentiment
6.5
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.6% compared to the previous year. The mindshare of SAS Data Integration Server is 0.9%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
SAS Data Integration Server0.9%
Other96.8%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
NN
Works at a financial services firm with 5,001-10,000 employees
Offloads processes on the server side but needs better installation syntax
One area for improvement is the installation process. Another point could be the syntax, as it sometimes involves using syntax names that are not intuitive. For example, to calculate the difference between two dates, the general syntax in SAS is called the data difference or data net function. However, another name is used, such as NF and INK. Without knowledge of SAS programming, it becomes unclear what these functions mean. It is not good to define function names this way.

Quotes from Members

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

Pros

"The solution can scale very easily."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"Azure Data Factory is a low code, no code platform, which is helpful."
"The security of the agent that is installed on-premises is very good."
"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."
"Azure Data Factory is an integration tool, an orchestration service tool; it is for data integration for the cloud."
"Microsoft's technical support is responsive and quick to help."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."
"The solution offers very good data manipulation and loading."
"The solution is very stable."
"The most valuable feature of the solution is its amazing capabilities in regard to data handling."
 

Cons

"The only thing that we're struggling with is increasing the competency of my team, so we think that the Microsoft documentation is too complicated."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"The performance and stability are touch and go."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"I do not have any notes for improvement."
"Some known bugs and issues with Azure Data Factory could be rectified."
"From my perspective, the pricing seems like it could be more user-friendly."
"Something that could improve is writing SQL to integration studio because it is not that straightforward. There should be better integration with other software."
"The initial setup of SAS Data Integration Server was complex."
"So I would like to see improved integration with other software."
"One area for improvement is the installation process."
"The transform tool has limited access. They should make it more flexible."
"The initial setup had issues, and even after using it for about one year, it was still not fixed."
 

Pricing and Cost Advice

"Understanding the pricing model for Data Factory is quite complex."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The cost is based on the amount of data sets that we are ingesting."
"I would rate Data Factory's pricing nine out of ten."
"The pricing model is based on usage and is not cheap."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"I would not say that this product is overly expensive."
"I don't see a cost; it appears to be included in general support."
"It is an expensive program."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
9%
Computer Software Company
9%
Construction Company
6%
Financial Services Firm
25%
Construction Company
13%
Comms Service Provider
10%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
No data available
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
What needs improvement with SAS Data Integration Server?
One area for improvement is the installation process. Another point could be the syntax, as it sometimes involves using syntax names that are not intuitive. For example, to calculate the difference...
What is your primary use case for SAS Data Integration Server?
I am involved in the ETR job. My role is focused on executing the ETR job.
What advice do you have for others considering SAS Data Integration Server?
I use it without further details. For example, if I use SAS to connect to a NetEazt database or purchase a shared asset to ODBC, I can connect to any database with ODBC connection support. The over...
 

Also Known As

No data available
SAS Enterprise Data Integration Server, Enterprise Data Integration Server
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, West Midlands Police, XS Inc., Zenith Insurance
Find out what your peers are saying about Azure Data Factory vs. SAS Data Integration Server and other solutions. Updated: June 2026.
906,781 professionals have used our research since 2012.