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- Azure Data Factory-vs-Oracle Data Integrator
Compare Azure Data Factory and Oracle Data Integrator 
- Users report that Azure Data Factory excels in its ease of setup, scoring 9.0 compared to Oracle Data Integrator's 6.2, making it a preferred choice for teams looking to implement data integration solutions quickly.
- Reviewers mention that Azure Data Factory's extraction capabilities are rated at 9.1, highlighting its robust connectors and integration with various data sources, while Oracle Data Integrator, although strong, does not match this level of versatility.
- G2 users indicate that Azure Data Factory shines in automation features, scoring 9.2, with users praising its ability to schedule and trigger data workflows seamlessly, whereas Oracle Data Integrator's automation features are perceived as less intuitive.
- Users on G2 report that Azure Data Factory's transformation capabilities are rated at 9.3, with specific praise for its data flow and mapping features, while Oracle Data Integrator, rated at 8.6, is noted for its powerful transformation but with a steeper learning curve.
- Reviewers mention that Azure Data Factory's scalability is impressive, scoring 9.3, allowing businesses to handle increasing data volumes efficiently, while Oracle Data Integrator, although scalable, is often seen as more complex to manage at scale.
- Users say that the quality of support for Azure Data Factory is rated at 8.8, with many highlighting responsive customer service, while Oracle Data Integrator's support, rated at 8.2, is viewed as adequate but not as proactive in addressing user issues.
The most important thing with Data Factory is the ease of creating new pipelines. The pipelines are structures which you define to move data from Cloud to On-prem Sql Server. These pipelines can then be run at a particular time of day/week.
interface is not clean when using code free data movement
It is ability to create native code for the underlying data management technology. Flexibility of adding new technology stack by writing custom knowledge modules.
The development experience on odi is very complex in comparison to modern technologies like Informatica Cloud or powercenter as well. There too much of code complexity as well when developing even a simple project with odi. Also the setup process and...
The most important thing with Data Factory is the ease of creating new pipelines. The pipelines are structures which you define to move data from Cloud to On-prem Sql Server. These pipelines can then be run at a particular time of day/week.
It is ability to create native code for the underlying data management technology. Flexibility of adding new technology stack by writing custom knowledge modules.
interface is not clean when using code free data movement
The development experience on odi is very complex in comparison to modern technologies like Informatica Cloud or powercenter as well. There too much of code complexity as well when developing even a simple project with odi. Also the setup process and...
