Azure Data Factory vs SAS Data Integration Server comparison

Microsoft and SAS are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.2, while SAS is ranked #41 with an average rating of 7.0. Microsoft holds a 5.2% mindshare in DI, compared to SAS’s 0.6% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 83% of SAS users who would recommend it.

Azure Data Factory

Read 92 Azure Data Factory reviews

13,131 Views
9,192 Comparison Views

92% willing to recommend

SAS Data Integration Server

Read 4 SAS Data Integration Server reviews

842 Views
623 Comparison Views

83% willing to recommend

Azure Data Factory

SAS Data Integration Server

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAS Data Integration Server and Azure Data Factory compete in the data integration space. Azure Data Factory appears to have the upper hand due to its cloud-native design and diverse features, offering superior value for tech buyers.

Features: SAS Data Integration Server offers robust enterprise-level transformation capabilities, extensive integration options with SAS products, and excels in traditional ETL processes. Azure Data Factory is recognized for seamless Azure service integration, large-scale orchestration abilities, and user-friendly cloud management. It provides dynamic data transformation and management for hybrid environments.

Ease of Deployment and Customer Service: SAS Data Integration Server requires significant infrastructure and expertise, resulting in potentially complex deployments. It provides comprehensive customer support for intricate data integrations. Azure Data Factory offers a cloud-based, scalable deployment model, simplifying setup with easy configuration and efficient customer support. Its deployment process is more streamlined, benefiting businesses with quicker turnaround times.

Pricing and ROI: SAS Data Integration Server involves higher setup costs due to infrastructure needs but can lead to strong ROI in stable enterprise environments that rely on SAS ecosystems. Azure Data Factory’s pay-as-you-go model offers flexibility and lower upfront costs, making it cost-effective for businesses needing cloud scalability. It caters to variable workloads and delivers better ROI for modern, adaptive data strategies.

To learn more, read our detailed Azure Data Factory vs. SAS Data Integration Server Report (Updated: September 2025).

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

September 2025

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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

Ranking in other categories

Cloud Data Warehouse (2nd)

SAS Data Integration Server

Ranking in Data Integration

41st

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of Azure Data Factory is 5.2%, down from 11.0% compared to the previous year. The mindshare of SAS Data Integration Server is 0.6%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Azure Data Factory	5.2%
SAS Data Integration Server	0.6%
Other	94.2%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

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.

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reviewer2937544

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.

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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 feature is the copy activity."

"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."

"It is a complete ETL Solution."

"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."

"We haven't had any issues connecting it to other products."

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

"The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable."

"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."

More Azure Data Factory pros

"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 solution offers very good data manipulation and loading."

"The most valuable feature of the solution is its amazing capabilities in regard to data handling."

"A key feature allows us to enhance job performance by offloading processing to the server side, rather than processing on the server itself."

Cons

"The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."

"My only problem is the seamless connectivity with various other databases, for example, SAP."

"The product's technical support has certain shortcomings, making it an area where improvements are required."

"Real-time replication is required, and this is not a simple task."

"Data Factory's performance during heavy data processing isn't great."

"The setup and configuration process could be simplified."

"We have experienced some issues with the integration. This is an area that needs improvement."

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

More Azure Data Factory cons

"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."

"The initial setup of SAS Data Integration Server was complex."

"The transform tool has limited access. They should make it more flexible."

"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."

Pricing and Cost Advice

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"This is a cost-effective solution."

"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."

"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."

"Pricing is comparable, it's somewhere in the middle."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"The cost is based on the amount of data sets that we are ingesting."

More Azure Data Factory pricing and cost advice

"It is an expensive program."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Government

Financial Services Firm

29%

Computer Software Company

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	19
Large Enterprise	55

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.

See all answers

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...

See all answers

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...

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What needs improvement with SAS Data Integration Server?

See all answers

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.

See all answers

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...

See all answers

Comparisons

Snowflake vs Azure Data Factory

Compared 8% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 6% of the time

Informatica PowerCenter vs Azure Data Factory

Compared 6% of the time

FME vs Azure Data Factory

Compared 5% of the time

Palantir Foundry vs Azure Data Factory

Compared 5% of the time

More Azure Data Factory Competitors

SSIS vs SAS Data Integration Server

Compared 34% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 17% of the time

Palantir Foundry vs SAS Data Integration Server

Compared 15% of the time

AWS Database Migration Service vs SAS Data Integration Server

Compared 14% of the time

More SAS Data Integration Server Competitors

Product Reports

Buyer's Guide

Azure Data Factory

October 2025

Download Azure Data Factory product report

Buyer's Guide

Data Integration

October 2025

Download SAS Data Integration Server product report

Also Known As

No data available

SAS Enterprise Data Integration Server, Enterprise Data Integration Server

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

SAS Data Integration Server is a powerful, configurable and comprehensive solution that can meet a wide variety of data integration requirements, from small tactical projects to strategic business initiatives. It can access virtually all data sources, support data warehousing, migration, synchronization, federation and provisioning initiatives. It can support both batch-oriented and real-time master data management solutions. It can create reusable data integration services in support of service-oriented architectures and data governance and extract, cleanse, transform, conform, aggregate, load and manage data.

SAS

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

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

September 2025

Free Report: Azure Data Factory vs. SAS Data Integration Server

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