Azure Data Factory Reviews

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.

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."

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.

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.

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.

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.

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.