Hi all,
Tired of paying the data movement tax or wrestling with complex manual pipeline configs?
I just published a new Medium article and open-sourced a framework that fully automates Databricks Lakeflow Connect pipelines for CDC-enabled databases using a simple YAML configuration.
Instead of writing verbose Databricks Asset Bundles by hand, this Python-driven tool automatically generates your deployment code, Unity Catalog setup scripts, and handles complex multi-destination routing right out of the box.
Key benefits of this approach:
Multi-Destination Routing Send different source tables to specific, domain-organized Bronze schemas from a single connection.
Native CDC Performance Leverage Lakeflow Connects serverless architecture for highly efficient, incremental ingestion. This means no more paralyzing full-table scans.
Massive Cost Savings Retire expensive third-party ETL tools and take advantage of Databricks free 100 DBU per day tier for Lakeflow Connect.
Whether you are ingesting data from SQL Server, PostgreSQL, or MySQL, this framework drastically cuts down boilerplate deployment code so you can focus on building your lakehouse.
Read the full breakdown on Medium: Automating Databricks Lakeflow Connect Pipelines for CDC Databases
Check out the code and try it yourself on GitHub: https://github.com/ShamenParis/databricks-dbs-gen/tree/main/lakeflow-connect
Let me know what you think in the comments. How is your team currently handling CDC ingestion into Databricks?
#Databricks #DataEngineering #LakeflowConnect #ETL #DataArchitecture #DataLakehouse #Python #CDC #DataIntegration
