Azure Data Factory vs SAS Data Integration Server comparison

Microsoft and SAS are both solutions in the Data Integration category. Microsoft is ranked #3 with an average rating of 8.2, while SAS is ranked #39 with an average rating of 7.0. Microsoft holds a 2.8% mindshare in DI, compared to SAS’s 0.8% 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 94 Azure Data Factory reviews

10,752 Views
7,526 Comparison Views

92% willing to recommend

SAS Data Integration Server

Read 4 SAS Data Integration Server reviews

1,338 Views
1,017 Comparison Views

83% willing to recommend

Azure Data Factory

SAS Data Integration Server

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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: March 2026).

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

March 2026

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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

3rd

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

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

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of March 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.8%, down from 9.7% 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 Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.8%
SAS Data Integration Server	0.8%
Other	96.4%

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

"I like the basic features like the data-based pipelines."

"I value the integration capabilities with other platforms and software in Azure Data Factory the most."

"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."

"The data flows were beneficial, allowing us to perform multiple transformations."

"Data Factory's most valuable feature is Copy Activity."

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."

"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."

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."

"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."

Cons

"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."

"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."

"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."

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

"The pricing scheme is very complex and difficult to understand."

"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."

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

"Data Factory's cost is too high."

More Azure Data Factory cons

"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."

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

Pricing and Cost Advice

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

"The solution's pricing is competitive."

"The pricing model is based on usage and is not cheap."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

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

"Product is priced at the market standard."

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."

"Understanding the pricing model for Data Factory is quite complex."

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

12%

Computer Software Company

11%

Manufacturing Company

Government

Financial Services Firm

27%

Computer Software Company

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	20
Large Enterprise	57

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...

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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.

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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

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Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

March 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

February 2026

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

March 2026

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

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