A good things about Azure Data Factory is its easy integration with strong integration with veriety of data sources. Building pipelines are the easiest one, even for the complex workflows and monitoring data movement and failure is very convenient for day to day work. Review collected by and hosted on G2.com.

The only thing looks difficult about Azure Data Factory is debugging is not very user friendly sometimes. The errors/ issues are not clear always and complex pipeline become too difficult to manage. Ratio of pricing is depends on how optimised the pipeline used. Review collected by and hosted on G2.com.

It enables scalable data integration between on-premises and cloud sources without intensive infrastructure management. Mapping data flows make complex transformations efficient and intuitive. I also appreciate the monitoring and control features, which provide clear visibility into pipeline executions. Review collected by and hosted on G2.com.

Debugging and error messages are not always clear, which can make troubleshooting time-consuming. Pricing can also be difficult to estimate, as the serverless model relies on activity execution and data movement. Review collected by and hosted on G2.com.

Azure data factory is very powerful when it comes to data integration at scale from data sources like Azure blob storage and Azure SQL databases. The ability to create and run pipeline from SDK is also a very good feature to have implementation. Review collected by and hosted on G2.com.

The private networking setup is bit convoluted from administration standpoint. we had issues initially making Azure data factory working privately with rest of our Azure native resources. Review collected by and hosted on G2.com.

Its ability to orchestrate and automate complex data integration workflows at scale. Its low-code, visual interface makes it easy to build and monitor pipelines, while its seamless integration with a wide range of data sources—both on-premises and cloud—enables reliable end-to-end data movement. Additionally, features like built-in scheduling, monitoring, error handling, and integration with other Azure services make it a robust and scalable solution for enterprise data engineering needs. Review collected by and hosted on G2.com.

While Azure Data Factory is a powerful orchestration tool, some limitations include limited debugging capabilities for complex pipelines and the lack of advanced transformation features compared to dedicated data processing engines like Spark. Version control and CI/CD integration can also feel less intuitive, especially for large teams, and troubleshooting performance or runtime issues can sometimes require switching between multiple monitoring views. Additionally, costs can increase as pipelines grow in complexity and frequency, requiring careful optimization and governance. Review collected by and hosted on G2.com.

Azure Data Factories have been heavily implemented in our Organization and most of them are used for ETL/ELT, parsing data, etc

I use the connectors for storage i.e. Blob and ADLS connector for data ingestion and data lake architecture. Review collected by and hosted on G2.com.

ADFs have latency hence real time streaming is an issue. Review collected by and hosted on G2.com.

Schedules and various types of schedules available in ADF. Review collected by and hosted on G2.com.

We can’t see all our pipeline activities in single page while monitoring. Also data gets erased after 50 days Review collected by and hosted on G2.com.

It's low code interface and integration flexibility is what I like best about azure data factory. You can connect to a wide range of data sources and create complex data pipelines visually without writing heavy code Review collected by and hosted on G2.com.

The debugging experience on the portal can be slow especially for large data flows. Also data flow mapping UI could be more responsive. Review collected by and hosted on G2.com.

I find Azure Data Factory user friendly - it's easy to navigate and find what I am looking for. Review collected by and hosted on G2.com.

Nothing I particularly dislike - haven't used many similar tools. Review collected by and hosted on G2.com.

Orchestrating processes by using various activities within Data Factory. Review collected by and hosted on G2.com.

complex pipeline structure and hard to track Review collected by and hosted on G2.com.

Linked services to connect to all types of services Review collected by and hosted on G2.com.

Simple control flow becomes very complex to achieve Review collected by and hosted on G2.com.