Build Reckon-Connected ETL Processes in Google Data Fusion

Ready to get started?

Download for a free trial:

Download Now

Learn more:

Reckon JDBC Driver

Complete read-write access to Reckon enables developers to search (Customers, Transactions, Invoices, Sales Receipts, etc.), update items, edit customers, and more, from any Java/J2EE application.



Load the CData JDBC Driver into Google Data Fusion and create ETL processes with access live Reckon data.

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

Upload the CData JDBC Driver for Reckon to Google Data Fusion

Upload the CData JDBC Driver for Reckon to your Google Data Fusion instance to work with live Reckon 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: cdatareckon-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.reckon) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.reckon.ReckonDriver)
  5. Click "Finish"

Connect to Reckon Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Reckon 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-reckon)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for Reckon. For example:

      jdbc:reckon:RTK=5246...;User=RCUser;Password=RCUserPassword;URL=http://remotehost:8166;

      When you are connecting to a local Reckon instance, you do not need to set any connection properties.

      Requests to Reckon are made through the Remote Connector. The Remote Connector runs on the same machine as Reckon and accepts connections through a lightweight, embedded Web server. The server supports SSL/TLS, enabling users to connect securely from remote machines.

      The first time you connect to your company file, you will need to authorize the Remote Connector with Reckon. See the "Getting Started" chapter of the help documentation for a guide.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.reckon.jar

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

    • Set Import Query to a SQL query that will extract the data you want from Reckon, i.e.:
      SELECT * FROM Customers
  4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
  5. Click "Properties" on the BigQuery sink to edit the properties
    • Set the Label
    • Set Reference Name to a value like reckon-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 Reckon data into

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

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