How to connect and process QuickBooks Data from Azure Databricks



Use CData, Azure, and Databricks to perform data engineering and data science on live QuickBooks Data

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live QuickBooks data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live QuickBooks data in Databricks.

With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live QuickBooks data. When you issue complex SQL queries to QuickBooks, the driver pushes supported SQL operations, like filters and aggregations, directly to QuickBooks 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 QuickBooks data using native data types.

About QuickBooks Data Integration

CData simplifies access and integration of live QuickBooks data. Our customers leverage CData connectivity to:

  • Access both local and remote company files.
  • Connect across editions and regions: QuickBooks Premier, Professional, Enterprise, and Simple Start edition 2002+, as well as Canada, New Zealand, Australia, and UK editions from 2003+.
  • Use SQL stored procedures to perform actions like voiding or clearing transactions, merging lists, searching entities, and more.

Customers regularly integrate their QuickBooks data with preferred tools, like Power BI, Tableau, or Excel, and integrate QuickBooks data into their database or data warehouse.


Getting Started


Install the CData JDBC Driver in Azure

To work with live QuickBooks data in Databricks, install the driver on your Azure cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "DBFS" as the Library Source and "JAR" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.quickbooks.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for QuickBooks\lib).

Connect to QuickBooks from Databricks

With the JAR file installed, we are ready to work with live QuickBooks data in Databricks. Start by creating a new notebook in your workspace. Name the workbook, make sure Python is selected as the language (which should be by default), click on Connect and under General Compute select the cluster where you installed the JDBC driver (should be selected by default).

Configure the Connection to QuickBooks

Connect to QuickBooks by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.quickbooks.QuickBooksDriver"
url = "jdbc:quickbooks:RTK=5246...;URL=http://remotehost:8166;User=admin;Password=admin123;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.quickbooks.jar

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

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

Requests are made to QuickBooks through the Remote Connector. The Remote Connector runs on the same machine as QuickBooks 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, you will need to authorize the Remote Connector with QuickBooks. See the "Getting Started" chapter of the help documentation for a guide.

Load QuickBooks Data

Once the connection is configured, you can load QuickBooks data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Customers") \
	.load ()

Display QuickBooks Data

Check the loaded QuickBooks data by calling the display function.

display (remote_table.select ("Name"))

Analyze QuickBooks Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the QuickBooks data for analysis.

result = spark.sql("SELECT Name, CustomerBalance FROM SAMPLE_VIEW")

The data from QuickBooks is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for QuickBooks and start working with your live QuickBooks data in Azure Databricks. Reach out to our Support Team if you have any questions.

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