Data Pipeline for Bringing Data from Oracle Fusion to Azure Databricks

[Pratikmsbsvm]

I am trying to bring Oracle Fusion (SCM, HCM, Finance) Data and push to ADLS Gen2. Databricks used for Data Transformation and Powerbi used for Reports Visualization.

I have 3 Option.

Option 1 :

Option 2 : 

Option 3

May someone please help me which is best enterprise cost effective approach and why. Or any Other way to achieve this effectively.

Thanks a lot

[bianca_unifeye]

@Raman_Unifeye this one is for you 😁

[bianca_unifeye · Accepted solution]

My preference is option 1 

• Delta Sharing is the most efficient and secure integration between Databricks and external systems.

• No JDBC bottlenecks (no long-running queries, no network saturation).

• Data shared as Delta format, which is natively optimized for Databricks.

• Lower operational overhead — Databricks reads the Delta Shares directly.

• Good for large volumes (Finance, SCM, HCM typically generate big datasets).

• Strong governance and lineage support.

Also I don't like to use JDBC, I avoid using it unless there are no other options

• Not scalable for large Oracle Fusion workloads.

• JDBC pulls are:

  • slow

  • stateful

  • prone to timeouts

  • difficult to parallelize

  • expensive for large history loads

• High latency for production-grade pipelines.

• You must manage incremental logic manually (ROWIDs, timestamps, etc.).

[Raman_Unifeye]

Option-1 using Oracle's Bulk extraction utility BICC. It can directly export the extracted data files (typically CSV) to Oracle cloud storage destination and then you could use ADF to get it copied over to ADLS.