Stream Salesforce Pardot Data into Apache Kafka Topics

Apache Kafka is an open-source stream processing platform that is primarily used for building real-time data pipelines and event-driven applications. When paired with the CData JDBC Driver for Salesforce Pardot, Kafka can work with live Salesforce Pardot data. This article describes how to connect, access and stream Salesforce Pardot data into Apache Kafka Topics and to start Confluent Control Center to help users secure, manage, and monitor the Salesforce Pardot data received using Kafka infrastructure in the Confluent Platform.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Salesforce Pardot data. When you issue complex SQL queries to Salesforce Pardot, the driver pushes supported SQL operations, like filters and aggregations, directly to Salesforce Pardot and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Salesforce Pardot data using native data types.

Prerequisites

Before connecting the CData JDBC Driver for streaming Salesforce Pardot data in Apache Kafka Topics, install and configure the following in the client Linux-based system.

1. Confluent Platform for Apache Kafka
2. Confluent Hub CLI Installation
3. Self-Managed Kafka JDBC Source Connector for Confluent Platform

Define a New JDBC Connection to Salesforce Pardot data

1. Download CData JDBC Driver for Salesforce Pardot on a Linux-based system
2. Follow the given instructions to create a new directory extract all the driver contents into it:
   1. Create a new directory named Salesforce Pardot mkdir SalesforcePardot
   2. Move the downloaded driver file (.zip) into this new directory mv SalesforcePardotJDBCDriver.zip SalesforcePardot/
   3. Unzip the CData SalesforcePardotJDBCDriver contents into this new directory unzip SalesforcePardotJDBCDriver.zip
3. Open the Salesforce Pardot directory and navigate to the lib folder ls cd lib/
4. Copy the contents of the lib folder of Salesforce Pardot into the lib folder of Kafka Connect JDBC. Check the Kafka Connect JDBC folder contents to confirm that the cdata.jdbc.salesforcepardot.jar file is successfully copied into the lib folder cp * ../../confluent-7.5.0/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/ cd ../../confluent-7.5.0/share/confluent-hub-components/confluentinc-kafka-connect-jdbc/lib/
5. Install the CData Salesforce Pardot JDBC driver license using the given command, followed by your Name and Email ID java -jar cdata.jdbc.salesforcepardot.jar -l
6. Enter the product key or "TRIAL" (In the scenarios of license expiry, please contact our CData Support team)
7. Start the Confluent local services using the command: confluent local services start

   This starts all the Confluent Services like Zookeeper, Kafka, Schema Registry, Kafka REST, Kafka CONNECT, ksqlDB and Control Center. You are now ready to use the CData JDBC driver for Salesforce Pardot to stream messages using Kafka Connect Driver into Kafka Topics on ksqlDB.

8. Create the Kafka topics manually using a POST HTTP API Request: curl --location 'server_address:8083/connectors' --header 'Content-Type: application/json' --data '{ "name": "jdbc_source_cdata_salesforcepardot_01", "config": { "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector", "connection.url": "jdbc:salesforcepardot:ApiVersion=4;User=YourUsername;Password=YourPassword;UserKey=YourUserKey;", "topic.prefix": "salesforcepardot-01-", "mode": "bulk" } }'

   Let us understand the fields used in the HTTP POST body (shown above):

   • connector.class: Specifies the Java class of the Kafka Connect connector to be used.
   • connection.url: The JDBC connection URL to connect with Salesforce Pardot data.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.salesforcepardot.jar

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

     Salesforce Pardot supports connecting through API Version, Username, Password and User Key.

     • ApiVersion: The Salesforce Pardot API version which the provided account can access. Defaults to 4.
     • User: The Username of the Salesforce Pardot account.
     • Password: The Password of the Salesforce Pardot account.
     • UserKey: The unique User Key for the Salesforce Pardot account. This key does not expire.
     • IsDemoAccount (optional): Set to TRUE to connect to a demo account.

     Accessing the Pardot User Key

     The User Key of the current account may be accessed by going to Settings -> My Profile, under the API User Key row.

   • topic.prefix: A prefix that will be added to the Kafka topics created by the connector. It's set to "salesforcepardot-01-".
   • mode: Specifies the mode in which the connector operates. In this case, it's set to "bulk", which suggests that the connector is configured to perform bulk data transfer.

   This request adds all the tables/contents from Salesforce Pardot as Kafka Topics.

   Note: The IP Address (server) to POST the request (shown above) is the Linux Network IP Address.

9. Run ksqlDB and list the topics. Use the commands: ksql list topics;
10. To view the data inside the topics, type the SQL Statement: PRINT topic FROM BEGINNING;

Connecting with the Confluent Control Center

To access the Confluent Control Center user interface, ensure to run the "confluent local services" as described in the above section and type http://<server address>:9021/clusters/ on your local browser.

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for Salesforce Pardot and start streaming Salesforce Pardot data into Apache Kafka. Reach out to our Support Team if you have any questions.