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 3.0% 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 93 Azure Data Factory reviews

11,065 Views
7,745 Comparison Views

92% willing to recommend

SAS Data Integration Server

Read 4 SAS Data Integration Server reviews

1,220 Views
927 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: February 2026).

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

February 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 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
Product	Market Share (%)
Azure Data Factory	3.0%
SAS Data Integration Server	0.8%
Other	96.2%

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

"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."

"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."

"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."

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."

"The flexibility that Azure Data Factory offers is great."

"It is a complete ETL Solution."

"It is easy to integrate."

More Azure Data Factory pros

"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."

"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 user interface could use improvement. It's not a major issue but it's something that can be improved."

"Data Factory's cost is too high."

"There are performance issues, particularly with the underlying compute, which should be configurable."

"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."

"Some of the optimization techniques are not scalable."

"Azure Data Factory uses many resources and has issues with parallel workflows."

"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."

"The number of standard adaptors could be extended further."

More Azure Data Factory cons

"The initial setup had issues, and even after using it for about one year, it was still not fixed."

"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."

"One area for improvement is the installation process."

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

"So I would like to see improved integration with other software."

Pricing and Cost Advice

"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."

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

"The solution is cheap."

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

"I would not say that this product is overly expensive."

"The price you pay is determined by how much you use it."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"It's not particularly expensive."

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

28%

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	19
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...

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Comparisons

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

Compared 6% of the time

Snowflake vs Azure Data Factory

Compared 6% of the time

FME vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 4% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 4% of the time

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SSIS vs SAS Data Integration Server

Compared 14% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 8% of the time

Axway AMPLIFY Application Integration vs SAS Data Integration Server

Compared 7% of the time

Stitch vs SAS Data Integration Server

Compared 7% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAS Data Integration Server

Compared 7% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

February 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

January 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

February 2026

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

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