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Azure Data Factory Reviews

Vendor: Microsoft
4.0 out of 5
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What is Azure Data Factory?

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.

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Azure Data Factory is the #2 ranked solution in top Cloud Data Warehouse solutions and #3 ranked solution in top Data Integration Tools. PeerSpot users give Azure Data Factory an average rating of 8.0 out of 10. Azure Data Factory is most commonly compared to Informatica Intelligent Data Management Cloud (IDMC): Azure Data Factory vs Informatica Intelligent Data Management Cloud (IDMC). Azure Data Factory is popular among the large enterprise segment, accounting for 65% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 13% of all views.
Buyer's Guide
Azure Data Factory
December 2025
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Azure Data Factory mindshare

Product category:
Data Integration
As of December 2025, the mindshare of Azure Data Factory in the Data Integration category stands at 3.7%, down from 10.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.7%
SSIS4.6%
Informatica PowerCenter4.4%
Other87.3%
Data Integration

PeerResearch reports based on Azure Data Factory reviews

TypeTitleDate
CategoryData IntegrationDec 29, 2025Download
ProductReviews, tips, and advice from real usersDec 29, 2025Download
ComparisonAzure Data Factory vs SSISDec 29, 2025Download
ComparisonAzure Data Factory vs Informatica Intelligent Data Management Cloud (IDMC)Dec 29, 2025Download
ComparisonAzure Data Factory vs Informatica PowerCenterDec 29, 2025Download
Suggested products
TitleRatingMindshareRecommending
Informatica Intelligent Data Management Cloud (IDMC)4.03.9%92%214 interviewsAdd to research
Databricks4.1N/A96%91 interviewsAdd to research
 
 
Key learnings from peers
Last updated Dec 7, 2025

Valuable Features

Azure Data Factory's valuable features include seamless data transformations, integration with multiple sources, and robust automation tools. Users appreciate its intuitive interface, support for SAP and SQL databases, and scalability. Its orchestration capabilities, drag-and-drop functionality, and integration with Azure services facilitate efficient ETL processes. Built-in connectors for over 100 sources and effective monitoring enhance productivity. Azure Data Factory's data migration, security features, and user-friendly design are highly beneficial to organizations.
  • "I value the integration capabilities with other platforms and software in Azure Data Factory the most."
  • "The most valuable feature I have found at Azure Data Factory is the data flow function."
  • "Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."

Room for Improvement

Azure Data Factory users express the need for improved integration with Azure services and better machine learning embedding. They desire enhancements in user interface simplicity, better scheduling, and error feedback. There is a call for reduced dependency on coding, improved performance, and lower costs. Users seek better integration with SAP and Oracle, clearer pricing models, and more comprehensive documentation. They also request real-time data capabilities and enhanced monitoring and debugging tools.
  • "They should work on optimizing their licensing model and pricing structure."
  • "There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
  • "The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score."

ROI

Azure Data Factory enhances efficiency by saving time and effort, showing promise in ROI. Many users highlight the integration's benefits, especially in data migration and infrastructure cost reduction. Some report savings of 20% to 30% over five years. Organizations appreciate its role in centralizing data, facilitating analysis, and improving client satisfaction. Its operational cost is significantly lower compared to previous solutions, at around 30%, and has reduced infrastructure burdens by 60%.

Pricing

Enterprise buyers find Azure Data Factory offers competitive and flexible pay-as-you-go pricing, primarily driven by usage and resource consumption. Users consider it affordable with costs potentially ranging from a few hundred to thousands per month, depending on data and compute needs. While platform integration may incur extra charges, many appreciate the transparency and lack of hidden fees. However, some perceive it as expensive, especially with increased data, making cost estimation complex and challenging.
  • "Azure products generally offer competitive pricing, suitable for diverse budget considerations."
  • "The solution is cheap."
  • "I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

Popular Use Cases

Users primarily utilize Azure Data Factory for data integration, ETL processes, and data warehousing. They deploy it to move, transform, and store data from multiple sources, including on-premises and cloud environments, to facilitate analytics, machine learning, and reporting. Many businesses enhance traditional data pipelines, manage complex data transformations, and enable seamless data migration, leveraging Microsoft's cloud services to meet evolving business needs efficiently.

Service and Support

Azure Data Factory's customer service and support are generally well-regarded. Many find them responsive, with active community assistance and good documentation. Some mention delays or satisfaction issues, noting slow support times or needing improved documentation. Several rely on partner relationships or community resources for resolutions. Technical support is rated variably from average to excellent, with some delays in technical resolution times but generally proficient assistance provided.

Deployment

Users found Azure Data Factory's initial setup mostly straightforward and easy. Deployment duration varied based on requirements, ranging from a few hours to several weeks. Setup complexity depended on factors like environment configuration and number of pipelines. While some required professional training or additional resources, others managed it effortlessly by leveraging Microsoft tools and support. Cloud deployment generally facilitated a quicker process, with some finding the initial phase challenging due to required configurations.

Scalability

Azure Data Factory offers impressive scalability, frequently rated eight out of ten by users. It's easy to scale due to its cloud-based nature, efficiently handling medium to large-scale projects. Many find it ideal for developers and engineers, not end users. Organizations successfully manage thousands of users, benefiting from its ability to accommodate high demand. Some mention cost and third-party integration challenges, though it remains popular for tight Azure integrations and reusable components.

Stability

Azure Data Factory demonstrates high stability with many users rating it between eight and nine out of ten. Most users report it as reliable, noting few issues with bugs or crashes. Stable performance is noted when dealing with well-configured cloud infrastructures. While some mention occasional instabilities during large data handling or due to Microsoft updates, the platform is effective for daily operations, including connecting data sources and running diverse processes and transformations.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Azure Data Factory Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business24
Midsize Enterprise16
Large Enterprise46
By reviewers
By visitors reading reviews
Company SizeCount
Small Business485
Midsize Enterprise291
Large Enterprise1419
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Government
7%
Retailer
6%
Healthcare Company
6%
Insurance Company
6%
Energy/Utilities Company
4%
Educational Organization
3%
Comms Service Provider
3%
Construction Company
3%
University
3%
Media Company
2%
Non Profit
2%
Performing Arts
2%
Consumer Goods Company
2%
Outsourcing Company
2%
Real Estate/Law Firm
2%
Legal Firm
1%
Transportation Company
1%
Wholesaler/Distributor
1%
Pharma/Biotech Company
1%
Hospitality Company
1%
Logistics Company
1%
Recreational Facilities/Services Company
1%
Marketing Services Firm
1%
Recruiting/Hr Firm
1%
Mining And Metals Company
1%

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Azure Data Factory 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

Related questions

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Which solution do you prefer: KNIME, Azure Synapse Analytics, or Azure Data Factory?
  • 16
How do Alteryx, Denod, and Azure Data Factory overlap (or complement) each other?
  • 12
Do you think Azure Data Factory’s price is fair?
  • 27
What kind of organizations use Azure Data Factory?
  • 23
Is Azure Data Factory a secure solution?
  • 34
How does Azure Data Factory compare with Informatica PowerCenter?
  • 44
How does Azure Data Factory compare with Informatica Cloud Data Integration?
  • 75
Which is better for Snowflake integration, Matillion ETL or Azure Data Factory (ADF) when hosted on Azure?
  • 34
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  • 10
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Product Categories

Product Categories
Data Integration
Cloud Data Warehouse

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Azure Data Factory Reviews Summary
Author infoRatingReview Summary
Director at a computer software company with 1,001-5,000 employees4.0I've used Azure Data Factory for over five years, valuing its data flow, integration, and reusable components, though I see room for improvement in transformations, AI insights, and real-time monitoring dashboards. I rate it an 8.
Data Engineer at Vthinktechnologies4.5We transitioned to Azure Data Factory from Informatica for cost efficiency, enhancing data transformation and integration tasks. Despite some challenges in cluster operations and Git services, the platform significantly lowers costs and improves dataset handling for reporting and AI.
Data Architect/Engineering manager at Intellias4.0I've used Azure Data Factory for five years, finding it effective for large data volumes and integrations, though monitoring and pricing could improve; setup is simple, and I rate it eight out of ten for enterprise data workflows.
Chief Analytics Officer at Idiro Analytics4.0I am a partner and reseller focusing on building data pipelines and analytics solutions. Azure Data Factory's interactive interface facilitates easy use, but improved API connectors for specific services like HubSpot CRM would enhance its functionality.
Solution Architect at Mercedes-Benz AG3.5I find Azure Data Factory valuable for its ability to handle large datasets with scalability. However, integration with third-party solutions like SAP needs improvement. Compared to Databricks, Azure Data Factory has advantages in scalability and price within Microsoft Azure.
Sr. Technical Architect at Hexaware Technologies Limited4.0As a solution architect, I use Azure Data Factory for three years as an ETL tool in presales. Its low code nature and integration ease are valuable, though performance issues and data governance could improve. Moving clients to the cloud reduces costs.
Data Governance/Data Engineering Manager at National Bank of Fujairah PJSC3.5We mainly use Azure Data Factory to migrate on-premises data to the cloud, benefiting from its integration with SQL pools and Databricks. However, for automation and streaming, we rely more on Informatica and Snowflake, as ADF is limited in these areas.
Data architect at Old Mutual4.0I implemented Azure Data Factory for cloud data processing, utilizing Azure Logic Apps and Azure Key Vault for orchestration and security. Its workflow automation and user-friendly interface expedited development, though monitoring capabilities and deployment processes could be improved for efficiency.