Integrating SQL Server Tables with Unity Catalog for Seamless Updates (Lakehouse Federation)

Introduction:

As Data Engineers, we often work with diverse systems to ingest and consolidate data into a unified platform, preparing it for analysis and reporting to derive valuable business insights. In my daily work, I primarily use Databricks , which has become my go-to tool for its efficiency and versatility. Recently, I discovered the immense value of Lakehouse Federation, which enables seamless integration with external systems like SQL Server. This feature allows us to read data directly from SQL Server and make it available in Unity Catalog as soon as the data is updated, ensuring real-time accessibility and streamlined data governance.

Benefits

In my experience, I’ve found several compelling benefits of using Lakehouse Federation that significantly enhance data workflows:

1. Elimination of Data Ingestion Overhead: By leveraging Lakehouse Federation, there’s no need to ingest data from SQL Server into Databricks. This reduces development time and simplifies the overall data pipeline.
2. Real-Time Data Accessibility: As soon as data is available in SQL Server, it becomes immediately accessible in Unity Catalog. This ensures that the latest data is always available for analysis without delays.
3. Streamlined Batch Processing: Daily batch processes no longer need to wait for data to be loaded into Databricks raw tables. Instead, you can directly access the SQL Server catalog, eliminating unnecessary wait times and improving efficiency.
4. Reduced Data Ingestion Time: By cutting out the step of moving data from SQL Server to Databricks raw tables, Lakehouse Federation significantly reduces the time spent on data ingestion, allowing teams to focus on higher-value tasks.
5. Improved Cost Efficiency: Since data is not duplicated or moved unnecessarily, storage and compute costs are optimized, making the solution more cost-effective.
6. Simplified Data Governance: With data accessible through Unity Catalog, governance and compliance are streamlined. You can enforce consistent access controls, auditing, and metadata management across both SQL Server and Databricks environments.
7. Enhanced Flexibility: Lakehouse Federation allows teams to work with data in its original location, reducing dependencies on data movement and enabling a more agile and flexible architecture.

Prerequisite

To use Lakehouse Federation, ensure the following are in place:

• A Databricks workspace with Unity Catalog enabled.
• Permissions to create connections in the Databricks workspace.
• Access for the Databricks workspace to connect to your SQL Server

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Example

Setting Up a Test Table in SQL Server: To demonstrate how Lakehouse Federation works, I started by creating a test table in SQL Server. I added a few sample records to this table, which will serve as the source data for our integration.

-- Create a  test table in SQL server
CREATE TABLE dbo.datalakehouse_test(
    Id INTEGER,
    ItemName VARCHAR(10),
    Amount DECIMAL(10,2)
);

-- Insert Records
INSERT INTO dbo.datalakehouse_test(Id, ItemName, Amount)
VALUES(1,'Apple',10.24);

-- Check the records
SELECT * FROM dbo.datalakehouse_test        

Setting Up the SQL Server Connection in Databricks: I’ve already configured the connection between SQL Server and Databricks. Once the connection was established, I verified the integration by checking the table. Here’s how it looks:

The data is now accessible in Unity Catalog, and as shown below, it mirrors the structure and content of the SQL Server table. This seamless integration ensures consistency and real-time access to the data without the need for duplication or complex transformations.

To demonstrate the real-time capabilities of Lakehouse Federation, a new record is added to the SQL Server table. Within moments, the updated data becomes visible in Databricks, showcasing the seamless synchronization between SQL Server and Unity Catalog.

The newly added record is now instantly available in Unity Catalog, demonstrating the power of Lakehouse Federation to provide real-time access to data without the need for manual intervention or delays.

In this example, I won’t cover the setup of permissions, masking of PII (Personally Identifiable Information), or other security configurations. However, you can implement all necessary security measures as you would in a standard workflow to ensure data protection and compliance

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Conclusion

Lakehouse Federation bridges the gap between SQL Server and Databricks, enabling real-time data access and eliminating the need for complex data ingestion processes. By leveraging Unity Catalog, organizations can ensure seamless data synchronization, improved efficiency, and streamlined governance. Whether you’re working with real-time analytics, reporting, or data-driven decision-making, Lakehouse Federation offers a powerful solution to modernize your data architecture. Start exploring its capabilities today to unlock faster insights and drive greater business value.