Azure Data Factory vs SAS Access comparison

Microsoft and SAS are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 7.9, while SAS is ranked #59. Microsoft holds a 2.3% mindshare in DI, compared to SAS’s 0.8% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of SAS users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

SAS Access

Read 3 SAS Access reviews

2,125 Views
1,679 Comparison Views

100% willing to recommend

Azure Data Factory

SAS Access

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Executive SummaryUpdated on Dec 19, 2024

SAS Access and Azure Data Factory compete in the data integration tools category. Based on their abilities in cloud environments, Azure Data Factory appears to have the upper hand due to its comprehensive cloud-based features.

Features: SAS Access provides strong data connectivity, compatibility with SAS technologies, and integration within SAS environments. Azure Data Factory offers extensive cloud service integration, automated workflows, and supports a range of data formats.

Ease of Deployment and Customer Service: SAS Access is supported by detailed deployment guidelines and robust technical support, particularly for on-premises systems. Azure Data Factory provides flexible deployment options with comprehensive online support resources and documentation, suiting cloud-native environments well.

Pricing and ROI: SAS Access may incur higher setup costs unless organizations already employ SAS systems, offering good ROI within SAS ecosystems. Azure Data Factory features a subscription-based pricing model, delivering cost-effectiveness and scalability, with high ROI for enterprises leveraging cloud technology.

To learn more, read our detailed Azure Data Factory vs. SAS Access Report (Updated: August 2026).

Buyer's Guide

Azure Data Factory vs. SAS Access

August 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

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

SAS Access

Ranking in Data Integration

59th

Average Rating

9.0

Reviews Sentiment

7.5

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 Access is 0.8%, up from 0.4% 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 Access	0.8%
Other	96.9%

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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Robert Heck

Co Owner at Hecht und Heck GmbH

The solution is stable, scalable, and flexible

I rate the solution eight out of ten. The number of people required to maintain the solution is dependent on the other applications running. The solution in itself does not require a lot of maintenance. The solution is flexible and I recommend it when you have more complex applications with special requirements.

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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

"It is easy to integrate."

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."

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

"The solution has a good interface and the integration with GitHub is very useful."

"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."

"The data is more scalable."

"The data copy template is a valuable feature, and with the pipeline template, it takes only a few clicks for the on-premises data to come in."

"The most valuable features are data transformations."

More Azure Data Factory pros

"The most valuable feature is you have native access to the external databases."

"The SAS/ACCESS ability to connect creates an elegant simplicity."

"The most valuable part of SAS/ACCESS is what it is made for: connecting to remote systems that are not part of your physical SAS environment."

"The most valuable aspect of the solution is the ease of access to the data in those databases."

Cons

"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."

"As far as customer service and support with Azure Data Factory, we are not always satisfied with the response time."

"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."

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

"Azure Data Factory's pricing in terms of utilization could be improved."

"Technical support isn't the best, as it's a bit delayed at times. Whenever we need some urgent support, wherein we have to restart or something has stuck, it takes a bit of time."

"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."

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

More Azure Data Factory cons

"The primary way that this product can be improved is by adjusting their pricing model."

"I can't really recall any missing feature or general improvement that is needed. We don't really add too many new kinds of databases and therefore our needs are already met."

"The solution can provide access to the newer databases that come out sooner."

"The pricing model needs to be reconsidered and adjusted."

"The solution's pricing and licensing are expensive."

Pricing and Cost Advice

"The solution's pricing is competitive."

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

"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."

"Pricing appears to be reasonable in my opinion."

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

"Pricing is comparable, it's somewhere in the middle."

"This is a cost-effective solution."

"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."

More Azure Data Factory pricing and cost advice

"The pricing model is complex and is based on modular packages as well as the size of the applicable environment."

"The solution's pricing and licensing are expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

11%

Manufacturing Company

Computer Software Company

Construction Company

18%

Financial Services Firm

10%

Manufacturing Company

Comms Service Provider

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.

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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Comparisons

Snowflake vs Azure Data Factory

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

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Toad Data Point vs SAS Access

Compared 9% of the time

Informatica PowerCenter vs SAS Access

Compared 9% of the time

Qlik Talend Cloud vs SAS Access

Compared 6% of the time

Upsolver vs SAS Access

Compared 6% of the time

SAP Business Data Cloud vs SAS Access

Compared 5% of the time

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Product Reports

Buyer's Guide

Azure Data Factory

August 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

August 2026

Download SAS Access product report

Also Known As

No data available

SAS/Access

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 Access connects users to data across platforms, enabling insights and analytics. It provides seamless access and integration for data processing and management, bridging the gap between extensive datasets and analytics capabilities.

SAS Access offers robust features that facilitate data access and integration, making it a preferred choice for organizations seeking to manage, manipulate, and analyze data spread across different storage systems. Users benefit from its ability to deliver comprehensive data access, enhancing efficiency and productivity. By reducing complexities in accessing distant or disparate data, SAS Access stands as a versatile tool for businesses that want to overcome data silos and drive analytics innovation.

What Are the Valuable Features of SAS Access?

Scalability: Efficient handling of large-scale data allows organizations to grow without data processing bottlenecks.
Compatibility: Offers compatibility with a wide range of data sources, including databases and third-party applications, facilitating seamless data integration.
Security: Ensures robust data security protocols to protect sensitive data and maintain compliance with industry standards.

What Benefits Should Be Considered in Reviews?

Improved Decision-Making: Access to diverse data sources bolsters decision-making with comprehensive insights.
Time Savings: Streamlined data access reduces time spent on data preparation, accelerating project timelines.
Cost Efficiency: Efficient data processing reduces infrastructure costs and optimizes resource usage.

In finance, SAS Access is used to streamline data reporting and analysis, providing essential insights for risk management. Retailers use it to merge customer data from disparate sources, enabling personalized marketing. Healthcare organizations utilize it to integrate patient data securely, improving care delivery and outcomes.

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

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Buyer's Guide

Azure Data Factory vs. SAS Access

August 2026

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