Hi @nchittampelly 

Follow these steps:

Use a Compatible JDBC Driver

• Use a suitable JDBC driver such as CData Oracle Sales Cloud JDBC or HCM Cloud JDBC driver.

Upload the Driver to Databricks

• Add the driver JAR to your cluster via the Libraries tab. For Unity Catalog or shared clusters, ensure it's accessible.

Ensure Network Connectivity

• Verify that your Databricks workspace has network access to the Oracle CRM Cloud endpoint (check firewall/proxy settings).

Set Up the Connection in Code

• Use Spark’s JDBC connector in your notebook. Example:
  
  df = spark.read.format("jdbc") \
  .option("url", "<jdbc_url>") \
  .option("driver", "<driver_class>") \
  .option("dbtable", "<table_name>") \
  .load()
  
  Test the connection first, then begin ingesting data as needed for analysis.
  
  Use Databricks Secrets to keep your credentials safe. Also, check if the driver is compatible with your Databricks runtime version.

Oracle CRM on Demand is a Cloud platform not a relational database.

Is there any proven solution for this requirement?

Oracle suite of of cloud platforms ( such as cusomer feedback system / CX) typically offer API endpoints . You'd want to use Databricks jobs to fetch from APIs at a cadence per your requirments to medallion layers from go from there - from AI/BI Genie dasboards to AgentBricks...the world is your oyster.