Try our new research platform with insights from 80,000+ expert users

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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
SAS Data Integration Server
Ranking in Data Integration
38th
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 January 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.2%, down from 10.0% compared to the previous year. The mindshare of SAS Data Integration Server is 0.7%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.2%
SAS Data Integration Server0.7%
Other96.1%
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 valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"The data flows were beneficial, allowing us to perform multiple transformations."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"We have found the bulk load feature very valuable."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"Its integrability with the rest of the activities on Azure is most valuable."
"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."
"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."
"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."
"The most valuable feature of the solution is its amazing capabilities in regard to data handling."
"The solution is very stable."
 

Cons

"There's space for improvement in the development process of the data pipelines."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."
"I have encountered a problem with the integration with third-party solutions, particularly with SAP."
"The Microsoft documentation is too complicated."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"When the record fails, it's tough to identify and log."
"One area for improvement is the installation process."
"The initial setup had issues, and even after using it for about one year, it was still not fixed."
"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."
"The initial setup of SAS Data Integration Server was complex."
"So I would like to see improved integration with other software."
 

Pricing and Cost Advice

"I would rate Data Factory's pricing nine out of ten."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Product is priced at the market standard."
"I would not say that this product is overly expensive."
"The price you pay is determined by how much you use it."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Understanding the pricing model for Data Factory is quite complex."
"It is an expensive program."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
881,082 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
9%
Government
7%
Financial Services Firm
26%
Computer Software Company
8%
Insurance Company
7%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
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: December 2025.
881,082 professionals have used our research since 2012.