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Our platform contains and ship the following JDBC drivers:
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- PostgreSQL (`postgresql v42.7.10`)
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- MariaDB (includes support for MySQL, `mariadb-java-client v3.5.7`)
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- Microsoft SQL Server (`mssql-jdbc v13.2.1.jre11`)
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- Snowflake (`snowflake-jdbc v3.28.0`)
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## Custom JDBC Driver
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In addition to the shipped default JDBC drivers custom JDBC drivers can be registered.
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The following steps describe how they are configured.
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### Download Custom JDBC Driver
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Download the respective JDBC driver for the Database Management Systems that need to be connected.
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[Integrations](../../../../build/integrations/index.md) provides links for well know system and at the same time lists those that are in active use with Corporate Memory.
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### Provide a Custom JDBC Driver
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Consult your solutions manager or DevOps specialist for options how to copy / inject additional files, namely the JDBC driver `jar`, into a Corporate Memory deployment.
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Depending on the specific deployment model used the suitable options differ, some possibilities:
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- the docker compose package `cmem-orchestration` mounts the folder `./conf/dataintegration/plugin/` into the DataIntegration container (this location is assumed in the configuration snippets below and mapped to the container internal path `/opt/cmem/eccenca-DataIntegration/dist/etc/dataintegration/conf/plugin/`),
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- a dedicated Build project into which the driver jar files are uploaded as project (file) resources,
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- dedicated file or resource mounts in a docker compose or helm/kubernets configuration.
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## Driver Registration
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A custom JDBC driver needs to be registered in the DataIntegration configuration file, `dataintegration.conf`, `spark.sql.options` section.
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The following example demonstrates how to register the custom JDBC driver for the Databricks data lakehouse:
They can be configured in the configuration dialog of the dataset, consult the documentation of your DBMS / JDBC driver for details about the [JDBC connection string](https://www.baeldung.com/java-jdbc-url-format).
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