Databricks is a leading AI cloud-native platform that unifies data engineering, machine learning, and analytics at scale.
Its powerful data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes.
Integrating Databricks with CData Connect AI
gives organizations live, real-time access to Bullhorn CRM data without the need for complex ETL pipelines or
data duplication—streamlining operations and reducing time-to-insights.
In this article, we'll walk through how to configure a secure, live connection from Databricks to Bullhorn CRM
using CData Connect AI. Once configured, you'll be able to access Bullhorn CRM data directly from Databricks notebooks
using standard SQL—enabling unified, real-time analytics across your data ecosystem.
Overview
Here is an overview of the simple steps:
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Step 1 — Connect and Configure:
In CData Connect AI, create a connection to your Bullhorn CRM source, configure user permissions,
and generate a Personal Access Token (PAT).
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Step 2 — Query from Databricks:
Install the CData JDBC driver in Databricks, configure your notebook with the connection details,
and run SQL queries to access live Bullhorn CRM data.
Prerequisites
Before you begin, make sure you have the following:
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An active Bullhorn CRM account.
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A CData Connect AI account. You can log in or
sign up for a free trial here.
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A Databricks account. Sign up or log in here.
Step 1: Connect and Configure a Bullhorn CRM Connection in CData Connect AI
1.1 Add a Connection to Bullhorn CRM
CData Connect AI uses a straightforward, point-and-click interface to connect to available data sources.
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Log into Connect AI, click Sources on the left, and then
click Add Connection in the top-right.
👁 Adding a Connection in CData Connect AI
- Select "Bullhorn CRM" from the Add Connection panel.
👁 Selecting a data source
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Enter the necessary authentication properties to connect to Bullhorn CRM.
Begin by providing your Bullhorn CRM account credentials in the following:
If you are uncertain about your data center code, codes like CLS2, CLS21, etc. are cluster IDs that are contained in a user's browser URL (address bar) once they are logged in.
Example: https://cls21.bullhornstaffing.com/BullhornSTAFFING/MainFrame.jsp?#no-ba... indicates that the logged in user is on CLS21.
Authenticating with OAuth
Bullhorn CRM uses the OAuth 2.0 authentication standard. To authenticate using OAuth, create and configure a custom OAuth app. See the Help documentation for more information.
👁 Configuring a connection (Salesforce is shown)
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Click Save & Test in the top-right.
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Navigate to the Permissions tab on the Bullhorn CRM Connection page
and update the user-based permissions based on your preferences.
👁 Updating permissions
1.2 Generate a Personal Access Token (PAT)
When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server,
a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. PAT functions as an
alternative to your login credentials for secure, token-based authentication. It is a best practice to
create a separate PAT for each service to maintain granularity of access.
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Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
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On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
👁 Creating a new PAT
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Note: The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
Step 2: Connect and Query Bullhorn CRM Data in Databricks
Follow these steps to establish a connection from Databricks to Bullhorn CRM.
You'll install the CData JDBC Driver for Connect AI, add the JAR file to your cluster, configure your notebooks,
and run SQL queries to access live Bullhorn CRM data data.
2.1 Install the CData JDBC Driver for Connect AI
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In CData Connect AI, click the Integrations page on the left.
Search for JDBC or Databricks, click Download,
and select the installer for your operating system.
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Once downloaded, run the installer and follow the instructions:
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For Windows: Run the setup file and follow the installation wizard.
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For Mac/Linux: Unpack the archive and move the folder to /opt or
/Applications. Make sure you have execute permissions.
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After installation, locate the JAR file in the installation directory:
2.2 Install the JAR File on Databricks
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Log in to Databricks. In the navigation pane, click Compute on the left. Start or create a compute cluster.
👁 Launching a compute cluster in Databricks
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Click on the running cluster, go to the Libraries tab, and click Install New at the top right.
👁 Accessing the Libraries tab in Databricks
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In the Install Library dialog, select DBFS, and drag and drop the
cdata.jdbc.connect.jar file. Click Install.
👁 Uploading the JDBC driver JAR to DBFS
2.3 Query Bullhorn CRM Data in a Databricks Notebook
Notebook Script 1 — Define JDBC Connection:
- Paste the following script into the notebook cell:
driver = "cdata.jdbc.connect.ConnectDriver"
url = "jdbc:connect:AuthScheme=Basic;User=your_username;Password=your_pat;URL=https://cloud.cdata.com/api/;DefaultCatalog=Your_Connection_Name;"
- Replace:
- your_username - With your CData Connect AI username
- your_pat - With your CData Connect AI Personal Access Token (PAT)
- Your_Connection_Name - With the name of your Connect AI data source, from the Sources page
- Run the script.
Notebook Script 2 — Load DataFrame from Bullhorn CRM data:
- Add a new cell for this second script. From the menu on the right side of your notebook, click Add cell below.
- Paste the following script into the new cell:
remote_table = spark.read.format("jdbc") \
.option("driver", "cdata.jdbc.connect.ConnectDriver") \
.option("url", "jdbc:connect:AuthScheme=Basic;User=your_username;Password=your_pat;URL=https://cloud.cdata.com/api/;DefaultCatalog=Your_Connection_Name;") \
.option("dbtable", "YOUR_SCHEMA.YOUR_TABLE") \
.load()
- Replace:
- your_username - With your CData Connect AI username
- your_pat - With your CData Connect AI Personal Access Token (PAT)
- Your_Connection_Name - With the name of your Connect AI data source, from the Sources page
- YOUR_SCHEMA.YOUR_TABLE - With your schema and table, for example, BullhornCRM.Candidate
- Run the script.
Notebook Script 3 — Preview Columns:
- Similarly, add a new cell for this third script.
- Paste the following script into the new cell:
display(remote_table.select("ColumnName1", "ColumnName2"))
- Replace ColumnName1 and ColumnName2 with the actual columns from your Bullhorn CRM structure (e.g. Id, CandidateName, etc.).
- Run the script.
👁 Previewing Bullhorn CRM data data in Databricks notebook
You can now explore, join, and analyze live Bullhorn CRM data directly within Databricks
notebooks—without needing to know the complexities of the back-end API and without replicating Bullhorn CRM data.
Try CData Connect AI Free for 14 Days
Ready to simplify real-time access to Bullhorn CRM data?
Start your free 14-day trial of CData Connect AI today
and experience seamless, live connectivity from Databricks to Bullhorn CRM.
Low code, zero infrastructure, zero replication — just seamless, secure access to your
most critical data and insights.