Azure Data Factory vs SAS Data Integration Server comparison

Azure Data Factory vs. SAS Data Integration Server

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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

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

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 August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% compared to the previous year. The mindshare of SAS Data Integration Server is 0.9%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.3%
SAS Data Integration Server	0.9%
Other	96.8%

Data Integration

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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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

"UI is easy to navigate and I can retrieve VTL code without knowing in-depth coding languages."

"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."

"It is easy to deploy workflows and schedule jobs."

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

"The initial setup is very quick and easy."

"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."

"Azure Data Factory is easy to use and integrates well, providing good classification to bring data from diverse parts of the data infrastructure, whether from CSV files coming from the Cisco server, MySQL, Excel machines, or local network data from remote files."

"It's extremely consistent."

More Azure Data Factory pros

"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."

"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."

Cons

"When the record fails, it's tough to identify and log."

"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."

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."

"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."

"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."

"I do not have any notes for improvement."

"I have not found any real shortcomings within the product."

"The product could provide more ways to import and export data."

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."

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

"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."

Pricing and Cost Advice

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

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

"I don't see a cost; it appears to be included in general support."

"The solution's pricing is competitive."

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

"ADF is cheaper compared to AWS."

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

"Product is priced at the market standard."

More Azure Data Factory pricing and cost advice

"It is an expensive program."

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910,409 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

Financial Services Firm

23%

Construction Company

13%

Comms Service Provider

11%

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	64

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.

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...

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...

What needs improvement with SAS Data Integration Server?

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.

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...

Snowflake vs Azure Data Factory

Comparisons

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) 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

Palantir Foundry vs SAS Data Integration Server

Compared 5% of the time

Oracle Data Integrator (ODI) vs SAS Data Integration Server

Compared 5% of the time

Informatica PowerCenter vs SAS Data Integration Server

Compared 5% of the time

More SAS Data Integration Server Competitors

Product Reports

Azure Data Factory

Download Azure Data Factory product report

Data Integration

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

Azure Data Factory vs. SAS Data Integration Server