Leverage Azure Data Factory to load data from Azure to Autonomous database
Oracle has recently launched Oracle Database Service for Microsoft Azure (ODSA) that allows users to easily integrate Oracle Cloud Infrastructure’s Database service into Azure cloud environment. ODSA’s interconnect and account linking services are provided at no cost. This partnership gives users more choice for multi cloud architecture. It further opens up the possibility of hybrid use cases by leveraging services from both cloud providers.
One such example is leveraging Azure Data Factory (ADF) with Autonomous database (ADB). ADF can be used to copy the data from various data sources located in Azure or on premise to an OCI autonomous database.
If the data sources are located inside Azure virtual network/on premise network/AWS VPC, we need a Azure self-hosted integration run time to connect the ADB.
Please note that if the data sources are managed cloud service in Azure, we may use Azure Integration Runtime.
Here we will discuss the connectivity process for a first use case such as using a self-hosted integration runtime.
This can be achieved by performing 3 simple steps:
Step #1
Configure a self-hosted integration runtime (IR) in Azure. This IR can be installed in Windows Server running on either Azure or OCI. In our case, we have installed this on OCI windows server.
Create Integration runtimes in ADF:
Configure Integration runtime in OCI windows server.
Download the software from the link above and follow the wizard as per the instructions.
Start the IR configuration manager.
Refresh the IR status in Azure portal and status should show as ‘running’
Step #2
We will leverage a TLS connection string in ADB to establish the connectivity. Download the wallet in c:\ drive of OCI windows server where we installed IR.
Step #3
Create a linked service in Azure ADF.
Test the connection.
In this way, users can bring data from non-Oracle environment to Oracle Autonomous Database. This not only accelerates the use of analytics from data residing from multi-cloud environments, but enterprises would also be more comfortable investing in multi-cloud environment for data and analytics use cases.
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