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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
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
SAS Data Integration Server
Ranking in Data Integration
36th
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 April 2025, in the Data Integration category, the mindshare of Azure Data Factory is 9.5%, down from 12.7% compared to the previous year. The mindshare of SAS Data Integration Server is 0.5%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
NN
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

"We use the solution to move data from on-premises to the cloud."
"The data is more scalable."
"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 data flows were beneficial, allowing us to perform multiple transformations."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"The flexibility that Azure Data Factory offers is great."
"I enjoy the ease of use for the backend JSON generator, the deployment solution, and the template management."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"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 solution is very stable."
"The most valuable feature of the solution is its amazing capabilities in regard to data handling."
 

Cons

"The number of standard adaptors could be extended further."
"Real-time replication is required, and this is not a simple task."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"Customer service is not satisfactory. Third-party personnel handle support and rely on a knowledge repository."
"The deployment should be easier."
"I have not found any real shortcomings within the product."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"Some prebuilt data source or data connection aspects are generic."
"The transform tool has limited access. They should make it more flexible."
"One area for improvement is the installation process."
"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."
"The initial setup had issues, and even after using it for about one year, it was still not fixed."
"So I would like to see improved integration with other software."
 

Pricing and Cost Advice

"Data Factory is expensive."
"The licensing cost is included in the Synapse."
"This is a cost-effective solution."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"I don't see a cost; it appears to be included in general support."
"The solution's pricing is competitive."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"The pricing is a bit on the higher end."
"It is an expensive program."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Financial Services Firm
26%
Computer Software Company
13%
Government
12%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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 do you like most about SAS Data Integration Server?
The most valuable feature of the solution is its amazing capabilities in regard to data handling.
What is your experience regarding pricing and costs for SAS Data Integration Server?
I don't handle the cost and budget part. From the tool's perspective, I can say that it is an amazing product.
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...
 

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: March 2025.
845,406 professionals have used our research since 2012.