No more typing reviews! Try our Samantha, our new voice AI agent.

Azure Data Factory vs SAS Data Integration Server comparison

Why PeerSpot?
 

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
97
Ranking in other categories
Cloud Data Warehouse (7th)
SAS Data Integration Server
Ranking in Data Integration
41st
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 September 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 5.5% compared to the previous year. The mindshare of SAS Data Integration Server is 0.9%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.2%
SAS Data Integration Server0.9%
Other96.9%
Data Integration
 

Featured Reviews

Kunal Das - PeerSpot reviewer
Test Engineer at Happiest Minds Technologies
Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling
If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.
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 most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"The solution has a good interface and the integration with GitHub is very useful."
"The solution can scale very easily."
"Data Factory itself is great, it's pretty straightforward, you can easily add sources, join and lookup information, etc., and the ease of use is pretty good."
"I think it makes it very easy to understand what data flow is and so on. You can leverage the user interface to do the different data flows, and it's great. I like it a lot."
"It is easy to deploy workflows and schedule jobs."
"The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions."
"The most valuable feature of the solution is its amazing capabilities in regard to data handling."
"The solution offers very good data manipulation and loading."
"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."
 

Cons

"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"Real-time replication is required, and this is not a simple task."
"The product integration with advanced coding options could cater to users needing more customization."
"The initial setup is not very straightforward."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"Some prebuilt data source or data connection aspects are generic."
"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."
"Something that could improve is writing SQL to integration studio because it is not that straightforward. There should be better integration with other software."
"One area for improvement is the installation process."
"The transform tool has limited access. They should make it more flexible."
 

Pricing and Cost Advice

"Data Factory is expensive."
"The cost is based on the amount of data sets that we are ingesting."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"I would not say that this product is overly expensive."
"The solution's pricing is competitive."
"Data Factory is affordable."
"I don't see a cost; it appears to be included in general support."
"It is an expensive program."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
912,069 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
8%
Construction Company
7%
Financial Services Firm
23%
Comms Service Provider
13%
Construction Company
13%
Computer Software Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise64
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: September 2026.
912,069 professionals have used our research since 2012.