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From DLT to Lakeflow Declarative Pipelines: A Practical Migration Playbook
How-ToDevOps

From DLT to Lakeflow Declarative Pipelines: A Practical Migration Playbook

via DZoneSeshendranath Balla Venkata

Delta Live Tables (DLT) has been a game-changer for building ETL pipelines on Databricks, providing a declarative framework that automates orchestration, infrastructure management, monitoring, and data quality in data pipelines. By simply defining how data should flow and be transformed, DLT allowed data engineers to focus on business logic rather than scheduling and dependency management. Databricks expanded and rebranded this capability under the broader Lakeflow initiative. The product formerly known as DLT is now Lakeflow Spark Declarative Pipelines (SDP), essentially the next evolution of DLT with additional features and alignment to open-source Spark. The existing DLT pipelines are largely compatible with Lakeflow ; your code will still run on the new platform without immediate changes. However, to fully leverage Lakeflow’s capabilities and future-proof your pipeline, it’s recommended that you update your code to the new API. This playbook provides a practical, engineer-focused g

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