MariaDB Connector for Azure Data Factory (Pipeline)

The MariaDB Connector enables you to connect to MariaDB, a very powerful relational database engine, whether it's the free and open-source Community Server or Enterprise Platform.

In this article you will learn how to quickly and efficiently integrate MariaDB data in Azure Data Factory (Pipeline) without coding. We will use high-performance MariaDB Connector to easily connect to MariaDB and then access the data inside Azure Data Factory (Pipeline).

Let's follow the steps below to see how we can accomplish that!

Download Documentation

Prerequisites

Before we begin, make sure you meet the following prerequisite:

If you already have a JRE installed, you can try using it too. However, if you experience any issues, we recommend using one of the distributions mentioned above (you can install an additional JRE next to the existing one; just don't forget to configure the default Java in the Windows Environment Variables).

Download MariaDB JDBC driver

To connect to MariaDB in Azure Data Factory (Pipeline), you will have to download JDBC driver for it, which we will use in later steps. Let's perform these little steps right away:

  1. Visit MariaDB website.
  2. Follow the instructions there, download the JDBC driver, and save it locally, e.g. to D:\Drivers\JDBC\mariadb-java-client.jar.
    It is recommended to use JDBC driver compiled for Java 8, if possible.
  3. Done! That was easy, wasn't it? Let's proceed to the next step.

Create ODBC Data Source (DSN) based on ZappySys JDBC Bridge Driver

Step-by-step instructions

To get data from MariaDB using Azure Data Factory (Pipeline) we first need to create a DSN (Data Source) which will access data from MariaDB. We will later be able to read data using Azure Data Factory (Pipeline). Perform these steps:

  1. Download and install ODBC PowerPack.

  2. Open ODBC Data Sources (x64):

    Open ODBC Data Source
  3. Create a User data source (User DSN) based on ZappySys JDBC Bridge Driver

    ZappySys JDBC Bridge Driver
    Create new User DSN for ZappySys JDBC Bridge Driver
    • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
    • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.
    Azure Data Factory (Pipeline) uses a Service Account, when a solution is deployed to production environment, therefore for production environment you have to create and use a System DSN.
  4. Now, we need to configure the JDBC connection in the new ODBC data source. Simply enter the Connection string, credentials, configure other settings, and then click Test Connection button to test the connection:

    MariadbDSN
    jdbc:mariadb://mariadb-instance-host-name:3306/MyDatabase
    D:\Drivers\JDBC\mariadb-java-client.jar
    root
    ****************
    []
    JDBC-ODBC Bridge driver data source settings

    Use these values when setting parameters:

    • Connection string: jdbc:mariadb://mariadb-instance-host-name:3306/MyDatabase
    • JDBC driver file(s): D:\Drivers\JDBC\mariadb-java-client.jar
    • User name: root
    • User password: ****************
    • Connection parameters: []

  5. You should see a message saying that connection test is successful:

    ODBC connection test is successful

    Otherwise, if you are getting an error, check out our Community for troubleshooting tips.

  6. We are at the point where we can preview a SQL query. For more SQL query examples visit JDBC Bridge documentation:

    MariadbDSN
    SELECT * FROM orders
    JDBC ODBC Bridge data source preview
    SELECT * FROM orders
    You can also click on the <Select Table> dropdown and select a table from the list.

    The ZappySys JDBC Bridge Driver acts as a transparent intermediary, passing SQL queries directly to the Trino JDBC driver, which then handles the query execution. This means the Bridge Driver simply relays the SQL query without altering it.

    Some JDBC drivers don't support INSERT/UPDATE/DELETE statements, so you may get an error saying "action is not supported" or a similar one. Please, be aware, this is not the limitation of ZappySys JDBC Bridge Driver, but is a limitation of the specific JDBC driver you are using.

  7. Click OK to finish creating the data source.

Video Tutorial

Read data in Azure Data Factory (ADF) from ODBC datasource (MariaDB)

  1. To start press New button:

    Create new Self-Hosted integration runtime
  2. Select "Azure, Self-Hosted" option:

    Create new Self-Hosted integration runtime
  3. Select "Self-Hosted" option:

    Create new Self-Hosted integration runtime
  4. Set a name, we will use "OnPremisesRuntime":

    Set a name for IR
  5. Download and install Microsoft Integration Runtime.

  6. Launch Integration Runtime and copy/paste Authentication Key from Integration Runtime configuration in Azure Portal:

    Copy/paste Authentication Key
  7. After finishing registering the Integration Runtime node, you should see a similar view:

    Check Integration Runtime node status
  8. Go back to Azure Portal and finish adding new Integration Runtime. You should see it was successfully added:

    Integration Runtime status
  9. Go to Linked services section and create a new Linked service based on ODBC:

    Add new Linked service
  10. Select "ODBC" service:

    Add new ODBC service
  11. Configure new ODBC service. Use the same DSN name we used in the previous step and copy it to Connection string box:

    MariadbDSN
    DSN=MariadbDSN
    Configure new ODBC service
  12. For created ODBC service create ODBC-based dataset:

    Add new ODBC dataset
  13. Go to your pipeline and add Copy data connector into the flow. In Source section use OdbcDataset we created as a source dataset:

    Set source in Copy data
  14. Then go to Sink section and select a destination/sink dataset. In this example we use precreated AzureBlobStorageDataset which saves data into an Azure Blob:

    Set sink in Copy data
  15. Finally, run the pipeline and see data being transferred from OdbcDataset to your destination dataset:

    Run the flow

Conclusion

In this article we showed you how to connect to MariaDB in Azure Data Factory (Pipeline) and integrate data without any coding, saving you time and effort. It's worth noting that ZappySys JDBC Bridge Driver allows you to connect not only to MariaDB, but to any Java application that supports JDBC (just use a different JDBC driver and configure it appropriately).

We encourage you to download MariaDB Connector for Azure Data Factory (Pipeline) and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download MariaDB Connector for Azure Data Factory (Pipeline) Documentation

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