Build Sybase-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Sybase enables users to access live Sybase data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Sybase data to any data source natively supported in Google Data Fusion, this article walks through piping data from Sybase to Google BigQuery,

Upload the CData JDBC Driver for Sybase to Google Data Fusion

Upload the CData JDBC Driver for Sybase to your Google Data Fusion instance to work with live Sybase data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatasybase-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.sybase) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.sybase.SybaseDriver)
5. Click "Finish"

Connect to Sybase Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Sybase data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-sybase)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Sybase. For example:
     
     jdbc:sybase:RTK=5246...;User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;Charset=iso_1;

     To connect to Sybase, specify the following connection properties:

     • Server: Set this to the name or network address of the Sybase database instance.
     • Database: Set this to the name of the Sybase database running on the specified Server.

     Optionally, you can also secure your connections with TLS/SSL by setting UseSSL to true.

     Sybase supports several methods for authentication including Password and Kerberos.

     Connect Using Password Authentication

     Set the AuthScheme to Password and set the following connection properties to use Sybase authentication.

     • User: Set this to the username of the authenticating Sybase user.
     • Password: Set this to the username of the authenticating Sybase user.

     Connect using LDAP Authentication

     To connect with LDAP authentication, you will need to configure Sybase server-side to use the LDAP authentication mechanism.

     After configuring Sybase for LDAP, you can connect using the same credentials as Password authentication.

     Connect Using Kerberos Authentication

     To leverage Kerberos authentication, begin by enabling it setting AuthScheme to Kerberos.

   See the Using Kerberos section in the Help documentation for more information on using Kerberos authentication.

   You can find an example connection string below: Server=MyServer;Port=MyPort;User=SampleUser;Password=SamplePassword;Database=MyDB;Kerberos=true;KerberosKDC=MyKDC;KerberosRealm=MYREALM.COM;KerberosSPN=server-name

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Sybase JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.sybase.jar

   Fill in the connection properties and copy the connection string to the clipboard.

4. Set Import Query to a SQL query that will extract the data you want from Sybase, i.e.:
   SELECT * FROM Products
5. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
6. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like sybase-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert Sybase data into

With the Source and Sink configured, you are ready to pipe Sybase data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Sybase and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Sybase pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Sybase and start working with your live Sybase data in Google Data Fusion today.