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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
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
39th
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 February 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. The mindshare of SAS Data Integration Server is 0.8%, 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 Factory3.0%
SAS Data Integration Server0.8%
Other96.2%
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 data flows were beneficial, allowing us to perform multiple transformations."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"It is beneficial that the solution is written with Spark as the back end."
"The solution handles large volumes of data very well. One of its best features is its ability to integrate data end-to-end, from pulling data from the source to accessing Databricks. This makes it quite useful for our needs."
"The flexibility that Azure Data Factory offers is great."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"Its integrability with the rest of the activities on Azure is most valuable."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"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."
"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."
 

Cons

"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."
"There's space for improvement in the development process of the data pipelines."
"The number of standard adaptors could be extended further."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"There is no built-in pipeline exit activity when encountering an error."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."
"It would be better if it had machine learning capabilities."
"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."
"The initial setup had issues, and even after using it for about one year, it was still not fixed."
"One area for improvement is the installation process."
"So I would like to see improved integration with other software."
 

Pricing and Cost Advice

"Pricing is comparable, it's somewhere in the middle."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"I don't see a cost; it appears to be included in general support."
"Data Factory is affordable."
"Product is priced at the market standard."
"The pricing is a bit on the higher end."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"It is an expensive program."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
9%
Government
6%
Financial Services Firm
27%
Computer Software Company
8%
Healthcare Company
7%
Manufacturing Company
6%
 

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: February 2026.
882,886 professionals have used our research since 2012.