Data Warehousing With Identity, PK/FK, Stored Proc and Loops

Explore the Latest SQL Warehouse Enhancements on Databricks Lakehouse

Databricks Lakehouse continues to evolve as the most powerful and user-friendly data warehouse platform. Recent updates make it easier than ever to manage complex SQL operations and accelerate migrations from on-prem or legacy data warehouses.

In this demo, we’ll walk through new capabilities that simplify schema design and data integrity:

• Auto-incrementing identity columns: Just insert data—Databricks will automatically handle ID generation.

• Primary key support: Enforce uniqueness and maintain data integrity.

• Foreign key constraints: Define relationships across tables with ease.

• Stored procedures and loops: Build more dynamic and procedural logic directly in SQL.

• Entity Relationship Diagram (ERD) support: Automatically visualize and manage table relationships with diagrams that are easy to maintain and evolve.

These features bring the convenience of traditional warehouses while unlocking the scalability and performance of the Lakehouse.

 

To install the demo, get a free Databricks workspace and execute the following two commands in a Python notebook

Dbdemos is a Python library that installs complete Databricks demos in your workspaces. Dbdemos will load and start notebooks, DLT pipelines, clusters, Databricks SQL dashboards, warehouse models … See how to use dbdemos

 

Dbdemos is distributed as a GitHub project.

For more details, please view the GitHub README.md file and follow the documentation.
Dbdemos is provided as is. See the License and Notice for more information.
Databricks does not offer official support for dbdemos and the associated assets.
For any issue, please open a ticket and the demo team will have a look on a best-effort basis.