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 94 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

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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: April 2026).

Buyer's Guide

Azure Data Factory vs. SAS Data Integration Server

April 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

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.

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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 that it's a monolithic data platform. This is why we propose these solutions."

"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."

"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."

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

"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."

"An excellent tool for pipeline orchestration."

"Data Factory lets us consolidate those steps into a single pipeline."

"The user interface is very good. It makes me feel very comfortable when I am using the tool."

More Azure Data Factory pros

"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 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 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

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

"To my mind, the solution needs to be more connectable to its own services."

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

"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."

"I find that Azure Data Factory is still maturing, so there are issues."

"The product integration with advanced coding options could cater to users needing more customization."

"The stability of Azure as a PaaS could be improved."

"Data Factory's monitorability could be better."

More Azure Data Factory cons

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

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

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

"One area for improvement is the installation process."

"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."

Pricing and Cost Advice

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

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

"The solution is cheap."

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

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

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

"The pricing is a bit on the higher end."

"This is a cost-effective solution."

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

10%

Manufacturing Company

Government

Financial Services Firm

26%

Construction Company

11%

Comms Service Provider

Computer Software 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

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

Compared 5% of the time

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 3% 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 7% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 5% 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

Informatica PowerCenter 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

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