Azure Data Factory vs SAS Data Integration Server comparison

Microsoft and SAS are both solutions in the Data Integration category. Microsoft is ranked #4 with an average rating of 8.2, while SAS is ranked #40 with an average rating of 7.0. Microsoft holds a 2.4% mindshare in DI, compared to SAS’s 0.9% 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 95 Azure Data Factory reviews

12,241 Views
8,446 Comparison Views

92% willing to recommend

SAS Data Integration Server

Read 4 SAS Data Integration Server reviews

1,902 Views
1,484 Comparison Views

83% willing to recommend

Azure Data Factory

SAS Data Integration Server

Comparison Buyer's Guide

Download the report

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: April 2026).

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

April 2026

Download the complete report

Helped 896,467 peers since 2012

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

4th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (5th)

SAS Data Integration Server

Ranking in Data Integration

40th

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of SAS Data Integration Server is 0.9%, 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	2.4%
SAS Data Integration Server	0.9%
Other	96.7%

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.

Read full review

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.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"If you have Azure as a cloud service and you want to perform ETL then Azure Data Factory is a product that I can recommend."

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."

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

"Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization."

"The reason that we implemented this product is for the full integration with the whole Azure environment."

"The most valuable part of this product is the ease of use, as it is easy to use and rather intuitive, and because it is easy to use, you can do things with it easily, making your work easier and therefore more valuable."

"It makes it easy to collect data from different sources."

"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."

More Azure Data Factory pros

"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."

"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

"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier."

"There's space for improvement in the development process of the data pipelines."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"The only challenge with Azure Data Factory is its exception-handling mechanism."

"The performance could be better. It would be better if Azure Data Factory could handle a higher load."

"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."

"There are limitations when processing more than one GD file."

"Some of the optimization techniques are not scalable."

More Azure Data Factory cons

"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."

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

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

"Something that could improve is writing SQL to integration studio because it is not that straightforward. There should be better 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

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

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

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

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

"ADF is cheaper compared to AWS."

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

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

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

More Azure Data Factory pricing and cost advice

"It is an expensive program."

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

896,467 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

10%

Manufacturing Company

Government

Financial Services Firm

27%

Construction Company

11%

Comms Service Provider

10%

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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...

See all answers

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 5% of the time

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

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

SSIS vs SAS Data Integration Server

Compared 8% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 5% of the time

Palantir Foundry vs SAS Data Integration Server

Compared 4% of the time

Axway AMPLIFY Application Integration vs SAS Data Integration Server

Compared 4% of the time

Matillion Data Productivity Cloud vs SAS Data Integration Server

Compared 4% of the time

More SAS Data Integration Server Competitors

Product Reports

Buyer's Guide

Azure Data Factory

May 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

May 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 automates and manages data integration processes, enabling efficient data management, transformation, and migration in enterprises. It provides a comprehensive suite for data-driven solutions.

Designed for extensive data management needs, SAS Data Integration Server supports seamless data integration, allowing users to access, run, and monitor data transformation processes. It is tailored to enhance data quality and streamline processes, serving industries reliant on precise data interpretation and utilization. With robust functionalities, it simplifies complex data environments, promoting productivity and reliability in data handling.

What are the key features of SAS Data Integration Server?

Data Profiling: Ensures data accuracy and quality through thorough analysis.
ETL Capabilities: Extracts, transforms, and loads data efficiently.
Metadata Management: Centralized control over data definitions and usage.
Data Lineage: Tracks data source origins and transformations for transparency.

What benefits and ROI should reviewers look for?

Improved Data Accuracy: Enhances decision-making with high-quality data.
Increased Efficiency: Reduces time and effort in data-related tasks.
Scalability: Adapts to growing business data demands seamlessly.
Reduced Costs: Optimizes resources, minimizing unnecessary expenditures.

SAS Data Integration Server finds applications across numerous industries, like finance and healthcare, where data integration and quality are critical. In finance, it helps manage vast amounts of transaction data, while in healthcare, it ensures accurate patient information management and reporting.

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

April 2026

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

Find out what your peers are saying about Azure Data Factory vs. SAS Data Integration Server and other solutions. Updated: April 2026.

DOWNLOAD NOW

896,467 professionals have used our research since 2012.

See our Azure Data Factory vs. SAS Data Integration Server report.

See our list of best Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.