Azure Data Factory Reviews

Name: Azure Data Factory
Brand: Microsoft
Rating: 4.0 (88 reviews)

Vendor: Microsoft

4.0 out of 5

88 reviews
92% willing to recommend

1,342 followers

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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 #1 ranked solution in top Data Integration Tools and #3 ranked solution in top Cloud Data Warehouse solutions. PeerSpot users give Azure Data Factory an average rating of 8.0 out of 10. Based on the analysis of the 88 most recent Azure Data Factory reviews, the overall sentiment is positive, with a sentiment score of 6.9. 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 70% 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.

Helped 824,121 peers since 2012

Featured reviews

Joy Maitra

Sr. Technical Architect at Hexaware Technologies Limited

Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.

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Thulani David Mngadi

Data architect at Old Mutual

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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Anil Jha

Director D&A at Iris Software Inc.

The primary use case is integrating data from different ERP systems and loading it into Azure Synapse for reporting. We use Power BI for the reporting side of it. We also have customers who are migrating to Azure Data Factory and we are assisting them with making the transition It is easy to…

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Azure Data Factory mindshare

Product category:

As of December 2024, the mindshare of Azure Data Factory in the Data Integration category stands at 11.0%, down from 13.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Data Integration

PeerAnalyst reports

Type	Title	Date
Category	Data Integration	Dec 29, 2024	Download
Product	Reviews, tips, and advice from real users	Dec 29, 2024	Download
Comparison	Azure Data Factory vs Informatica PowerCenter	Dec 29, 2024	Download
Comparison	Azure Data Factory vs Informatica Intelligent Data Management Cloud (IDMC)	Dec 29, 2024	Download
Comparison	Azure Data Factory vs SSIS	Dec 29, 2024	Download

Title	Rating	Mindshare	Recommending
Informatica Intelligent Data Management Cloud (IDMC)	4.0	N/A	93%	181 interviews Add to research
Informatica PowerCenter	4.0	11.0%	91%	80 interviews Add to research

Valuable Features

Azure Data Factory's most valuable features include extensive integration capabilities, ease of use with an intuitive interface, and scalability. It offers powerful ETL capabilities, a wide range of data connectors, and robust monitoring tools. Users appreciate the drag-and-drop functionality, efficient data flows, and seamless integration with other Azure services. It supports various data sources, allows easy transformation processes, and provides flexibility in automation and security settings.

"Azure Data Factory is a low code, no code platform, which is helpful."
"Azure Data Factory is a low code, no code platform, which is helpful."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."

Room for Improvement

Azure Data Factory requires better integration with machine learning and third-party services, improved user interface and error feedback, and enhanced pricing transparency. It should simplify the setup process and documentation. Performance issues, such as slow data processing and connectivity challenges, need addressing. Users also seek more out-of-the-box connectors, advanced monitoring capabilities, and real-time data handling. Debugging tools and API support should be expanded, as should its collaboration with other Azure services.

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"Some prebuilt data source or data connection aspects are generic."

ROI

Users express a positive impact from Azure Data Factory, noting significant time and effort savings that contribute to a favorable ROI. Some have seen a 20% to 30% return over five years. It aids in data migration and integration, leading to cost reductions and client satisfaction. Though formal ROI calculations are rare, the efficiency and insights gained often justify its usage. Large organizations acknowledge its importance despite not consistently tracking returns.

Pricing

Azure Data Factory offers a pay-as-you-go pricing model, making it cost-effective for enterprises, though predicting exact expenses can be challenging. Monthly costs vary widely, from a few hundred to thousands of dollars, based on usage and data processed. While largely affordable, some users find the pricing complex and potentially high without careful management. Additional cloud services might increase costs. Overall, Azure Data Factory is competitively priced compared to other providers, suitable for diverse budgets.

"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

Azure Data Factory is frequently used for data integration, data migration, data warehousing, and ETL processes. Users apply it to load data into Azure SQL databases, transform data in Azure Data Lake, connect different cloud and on-premises environments, and enable analytics and reporting with Power BI. It supports diverse use cases like extracting data from multiple sources, synchronizing databases, and orchestrating data workflows in hybrid environments.

Service and Support

Most users express satisfaction with Azure Data Factory's support, highlighting responsiveness and helpfulness. The community support and online resources are praised, though some find the documentation lacking. Response times can be delayed, with some finding customer service unsatisfactory. Paid support is noted as costly. Technical support is generally rated between seven and nine out of ten, with users appreciating Microsoft's efforts to resolve issues, despite occasional delays.

Deployment

Azure Data Factory's initial setup is generally straightforward, though its complexity can vary. Some users found it quick and simple, taking minutes to days, while others experienced more challenges, requiring weeks or months. Factors affecting complexity include integration with on-premises environments, data volume, and specific organizational requirements. Familiarity with Azure and DevOps practices is beneficial. Many found deploying in cloud environments easier, while some needed multiple team members for setup and maintenance.

Scalability

Azure Data Factory demonstrates impressive scalability with seamless expansion capabilities in cloud environments. Multiple organizations report ease of scaling, adaptable for both medium and large volumes of data and high user numbers. While most find scalability satisfactory, some pinpoint areas needing improvement, particularly for third-party integrations. The system efficiently supports diverse use cases, offering robust scalability, though its performance may vary based on data sources and workloads. Most users rate scalability high, noting efficient resource management.

Stability

Users report Azure Data Factory as highly stable, with most experiencing no major issues or downtime. The platform is reliable for both daily and continuous use. Occasional problems like connection timeouts and slow performance during high data volumes have been noted. Some highlight improvements over time, rating stability as eight or nine out of ten. While a few encounter minor glitches, most find the system dependable with varying satisfaction based on individual cloud setups and infrastructure.

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

By visitors reading reviews

Top industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Government

Energy/Utilities Company

Insurance Company

Retailer

Educational Organization

University

Comms Service Provider

Media Company

Construction Company

Real Estate/Law Firm

Non Profit

Legal Firm

Transportation Company

Wholesaler/Distributor

Hospitality Company

Pharma/Biotech Company

Logistics Company

Performing Arts

Consumer Goods Company

Outsourcing Company

Recreational Facilities/Services Company

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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