Azure Data Factory vs SAS Data Management comparison

Microsoft and SAS are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.1, while SAS is ranked #37 with an average rating of 7.5. Microsoft holds a 11.0% mindshare in DI, compared to SAS’s 0.8% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 87% of SAS users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

21,615 Views
17,232 Comparison Views

92% willing to recommend

SAS Data Management

Read 16 SAS Data Management reviews

1,195 Views
995 Comparison Views

87% willing to recommend

Azure Data Factory

SAS Data Management

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

SAS Data Management and Azure Data Factory are prominent competitors in the data management and integration sector. Azure Data Factory appears to have the upper hand due to its seamless integration with Azure services and user-friendly interface, despite potential improvements in other areas.

Features: SAS Data Management stands out for its comprehensive data quality and integration capabilities, providing a unified view of enterprise data and accommodating multiple data sources. It also excels in reporting and customization. Azure Data Factory offers robust ETL functionalities with a user-friendly visual interface, highlighting its drag-and-drop feature for data workflows. It provides flexibility and scalability with built-in connectors for diverse sources.

Room for Improvement: SAS Data Management is often criticized for its high cost with a complex licensing model. Connectivity issues requiring third-party solutions and limited integration flexibility are noted drawbacks, coupled with a need for better documentation and simplified installation. Azure Data Factory could enhance its complex pricing model, real-time processing capabilities, and some missing connectors. Its integration and support for streaming data are also areas that require significant improvement, along with performance and UI enhancements.

Ease of Deployment and Customer Service: SAS Data Management primarily runs on-premises and is noted for its reliable customer service, although the support knowledge base is sometimes seen as lacking. Azure Data Factory, leveraging cloud deployments, provides great flexibility and scalability, although it faces mixed reviews in customer service responsiveness and technical support depth.

Pricing and ROI: SAS Data Management is seen as expensive with a complex pricing structure, yet offers significant ROI in sectors requiring compliance. The investment is justified by its integration and data standardization capabilities. Azure Data Factory operates on a pay-as-you-go model that offers flexibility but can lead to high costs if not managed well. Its competitive pricing makes it accessible to various businesses and tends to yield favorable ROI due to efficient data processing, despite a complex pricing estimation.

To learn more, read our detailed Azure Data Factory vs. SAS Data Management Report (Updated: December 2024).

Buyer's Guide

Azure Data Factory vs. SAS Data Management

December 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

SAS Data Management

Ranking in Data Integration

37th

Average Rating

8.4

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Quality (11th), Data Governance (26th)

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of SAS Data Management is 0.8%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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Vivek Trivedi

Head finance transformation at Ahli United Bank Ksc

Has robust data governance capabilities and efficient financial alerting features

The platform's robust data governance capabilities ensure strong compliance with regulatory standards. Our dedicated data governance team is responsible for setting policies and monitoring data access and usage. Additionally, we have a Data Protection Officer (DPO) and an independent InfoSec team that work together to enforce these policies. This multi-layered approach ensures that data governance is effectively managed and compliant with all necessary regulations. It is integrated with SQL and Power BI servers for executive management dashboard reporting. This integration supports comprehensive data analysis and reporting needs, which was a key factor in our decision. The value of using vCenter lies in its comprehensive data infrastructure management. It significantly enhances our reporting, day-to-day decision-making, and analytics capabilities. Integrating SaaS with vCenter adds value by streamlining key functions and improving overall organizational efficiency. The solution can be considered expensive, particularly due to infrastructure, maintenance, and ownership costs. The long-term savings and efficiencies gained from using vCenter can justify the investment for large organizations. However, the high costs might not be justifiable for smaller organizations with less data and fewer resources. Conducting a thorough cost-benefit analysis based on the organization's specific needs and scale is recommended. I rate it an eight.

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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

"The overall performance is quite good."

"One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."

"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."

"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."

"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."

"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."

More Azure Data Factory pros

"If you compare it to SQL, the memory and development times are very quick."

"I am impressed with the tool's ability to customize."

"The product offers very good flexibility."

"The solution is very stable. We haven't faced any issues with glitches or bugs. We haven't had any crashes."

"The platform's robust data governance capabilities ensure strong compliance with regulatory standards."

"The technical support is excellent."

"The tool is reliable, quick, and powerful."

"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."

More SAS Data Management pros

Cons

"Real-time replication is required, and this is not a simple task."

"The support and the documentation can be improved."

"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."

"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."

"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."

"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."

"Some of the optimization techniques are not scalable."

"We have experienced some issues with the integration. This is an area that needs improvement."

More Azure Data Factory cons

"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."

"We find we often have to go back and re-train users when there are changes made to the solution because the changes are not intuitive."

"The solution is quite expensive and hard to install/configure."

"The pricing of the solution needs to be improved. They need to work to make it more affordable."

"I would like the tool to include the ability to automate the modifications of the integrations."

"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."

"Very little needs to improve but perhaps a nicer graphic interface and remaining competetive in the growing field of data analytics."

"Integration and cloud migration are areas where we see potential for improvement."

More SAS Data Management cons

Pricing and Cost Advice

"The solution is cheap."

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

"Data Factory is affordable."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"Data Factory is expensive."

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

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

"The price is fair."

More Azure Data Factory pricing and cost advice

"While it is even free for personal use on the cloud, it can be expensive for desktop installations and enterprise use."

"The solution is expensive."

"The licensing model for vCenter is a perpetual license with yearly payments."

"The tool is a bit expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

29%

Computer Software Company

13%

Insurance Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

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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 do you like most about SAS Data Management?

I am impressed with the tool's ability to customize.

See all answers

What is your experience regarding pricing and costs for SAS Data Management?

The licensing model for vCenter is a perpetual license with yearly payments. This model ensures continuous updates and support while managing initial setup costs.

See all answers

What needs improvement with SAS Data Management?

Integration and cloud migration are areas where we see potential for improvement. A more seamless integration process and transitioning to a cloud-based environment would enhance user-friendliness ...

See all answers

Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

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

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

Informatica PowerCenter vs SAS Data Management

Compared 18% of the time

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

Compared 13% of the time

Palantir Foundry vs SAS Data Management

Compared 13% of the time

Ab Initio Co>Operating System vs SAS Data Management

Compared 11% of the time

SSIS vs SAS Data Management

Compared 9% of the time

More SAS Data Management Competitors

Product Reports

Buyer's Guide

Azure Data Factory

December 2024

Download Azure Data Factory product report

Buyer's Guide

SAS Data Management

November 2024

Download SAS Data Management product report

Also Known As

No data available

SAS Data Management Platform, Data Management Platform, DataFlux

Learn More

Microsoft

SAS

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.

Every decision, every business move, every successful customer interaction - they all come down to high-quality, well-integrated data. If you don't have it, you don't win. SAS Data Management is an industry-leading solution built on a data quality platform that helps you improve, integrate and govern your data.

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

Data Management, 1-800-FLOWERS.COM, Absa, Aegon, Allianz Global Corporate & SpecialtyAusgrid, Bank of Queensland, Bell, BMC Software, Canada Post, Ceska pojistovna, Chantecler, Chubb Group of Insurance Companies, Credit Guarantee Corporation, Cr_dito y Cauci‹n, Delaware State Police, Deutsche Lufthansa, Directorate of Economics and Statistics, DSM, Enerjisa, ERGO Insurance Group, Florida Department of Corrections, Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare, Livzon Pharmaceutical Group, Los Angeles County, Miami Herald Media Company, Netherlands Enterprise Agency, New Zealand Ministry of Health, Nippon Paper, North Carolina Office of Information Technology Services, Orlando Magic, OTP Group, PITT OHIO, Plano Independent School District, RWE Poland, Spanish Air Force, Stockholm County Council, Telus, The Travel Corporation, Transitions Optical, Triad Analytic Solutions, UNIQA, US Census Bureau, US Department of Housing and Urban Development, USDA National Agricultural Statistics Service, West Midlands Police, XS Inc., Zenith Insurance

Buyer's Guide

Azure Data Factory vs. SAS Data Management

December 2024

Free Report: Azure Data Factory vs. SAS Data Management

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