How to connect and process Sage Intacct Data from Azure Databricks

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 Sage Intacct data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Sage Intacct data in Databricks.

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

Getting Started

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Install the CData JDBC Driver in Azure

To work with live Sage Intacct 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.sageintacct.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Intacct\lib).

Connect to Sage Intacct from Databricks

With the JAR file installed, we are ready to work with live Sage Intacct 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 Sage Intacct

Connect to Sage Intacct 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.sageintacct.SageIntacctDriver"
url = "jdbc:sageintacct:RTK=5246...;User=myusername;CompanyId=TestCompany;Password=mypassword;SenderId=Test;SenderPassword=abcde123;"

Built-in Connection String Designer

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

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

To connect using the Login method, the following connection properties are required: User, Password, CompanyId, SenderId and SenderPassword.

User, Password, and CompanyId are the credentials for the account you wish to connect to.

SenderId and SenderPassword are the Web Services credentials assigned to you by Sage Intacct.

Load Sage Intacct Data

Once the connection is configured, you can load Sage Intacct 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" , "Customer") \
	.load ()

Display Sage Intacct Data

Check the loaded Sage Intacct data by calling the display function.

display (remote_table.select ("Name"))

Analyze Sage Intacct 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 Sage Intacct data for analysis.

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

The data from Sage Intacct 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 Intacct and start working with your live Sage Intacct data in Azure Databricks. Reach out to our Support Team if you have any questions.