Connect to Databricks Data in ACL Analytics

Stanley Liu
Associate Technical Product Marketer

Connect to Databricks data via CData Connect AI in ACL Analytics to run your data analysis workflows with real-time access to Databricks data.

ACL Analytics, part of Diligent HighBond, is a powerful data analysis software primarily used for audit, risk management, and compliance. It enables professionals to examine and analyze large volumes of data to identify anomalies, trends, and potential risks or fraudulent activities.

CData Connect AI offers a dedicated cloud-to-cloud interface for Databricks, enabling analytics directly from live Databricks data within ACL Analytics, all without the need for data replication to a native database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to Databricks. This leverages server-side processing to swiftly deliver the requested Databricks data.

About Databricks Data Integration

Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:

Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.

While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.

Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.

Getting Started

Configure Databricks Connectivity for ACL Analytics

Connectivity to Databricks from ACL Analytics is made possible through CData Connect AI. To work with Databricks data from ACL Analytics, we start by creating and configuring a Databricks connection in CData Connect AI.

Log into Connect AI, click Sources, and then click Add Connection

Select "Databricks" from the Add Connection panel

Enter the necessary authentication properties to connect to Databricks. Enter the necessary authentication properties to connect to Databricks.
To connect to a Databricks cluster, set the properties as described below.

Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
- Server: Set to the Server Hostname of your Databricks cluster.
- HTTPPath: Set to the HTTP Path of your Databricks cluster.
- Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
Click Save & Test
Navigate to the Permissions tab in the Add Databricks Connection page and update the User-based permissions.

Add a Personal Access Token

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. It is best practice to create a separate PAT for each service to maintain granularity of access.

Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
On the Settings page, go to the Access Tokens section and click Create PAT.
Give the PAT a name and click Create.
The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Databricks data from ACL Analytics.

Connect to Databricks from ACL Analytics

The steps below outline connecting to CData Connect AI from ACL Analytics to create a new Databricks data source. The CData Connect AI Virtual SQL Server allows you to establish a connection to your data from integration tools that support connections to SQL servers. The Virtual SQL Server mimics the behavior of a traditional SQL server, and it supports a range of query options.

With your Analytics File open, select 'Import' --> 'Database and application'
Create a new SQL Server connection
Set the connection information
- Server: tds.cdata.com
- Port: 14333
- Auth Scheme: Password
- Username: a Connect AI user, for example, [email protected]
- Password: the PAT for the above Connect AI user
- Database: the name of your Databricks connection, for example, Databricks1
Click "Test Connection"
Click "OK"
You are now ready to work with your Databricks data in ACL Analytics!