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Using a custom JDBC driver with the on-premise JDBC Extractor

You can connect to your database using a custom JDBC driver to support environments or database versions not covered by native Uplink connections. This requires using an Uplink connection with the on-premise JDBC Extractor and a custom JDBC driver supplied by you.

Tip

The instructions on this page are needed only if you are required to connect to the Celonis Platform using a custom JDBC driver. If you are using an Uplink connection that is natively supported (or a Direct connection), you do not need to use a custom JDBC driver.

For a list of database extractors that natively support Uplink connections (and Direct connections), see Supported database types.

Prerequisites for using custom JDBC drivers

To use a custom JDBC driver with the JDBC Extractor, you must meet the following prerequisites:

Tip

For more information about on the integration steps for custom JDBC drivers, see Connecting using a custom JDBC driver with an Uplink connection.

Adding your custom JDBC driver

To enable the JDBC Extractor to communicate with your database, you must manually add your vendor-specific driver file to the extractor's file system.

To do so:

  1. Navigate to your Celonis JDBC Extractor directory.

  2. Create a directory named drivers (or alternatively any other name provided there is no period / full stop in the name).

  3. Place your database's JDBC driver file (.jar) in the drivers directory.

After placing the driver in the directory, use the -Dloader.path argument in the JDBC Extractor startup command or service configuration file to load the driver from that specific location.

Note

If you named the directory you stored your database's JDBC driver file (.jar) in other than drivers, ensure your use it as the -Dloader.path argument value.

For example:

java -Dloader.path=drivers -Dspring.config.location=application-local.yml -jar connector-jdbc.jar

The next integration step is to start the JDBC Extractor. For instructions on starting the JDBC Extractor, see Running the JDBC Extractor.