What’s new in dlt for Databricks: built-in staging, zero-config notebooks, no headaches

The Databricks destination in dlt has been updated with new features that simplify data ingestion tasks. The changes focus on three key areas: staging, notebook support, and environment configuration. A technical demo showcases a 30-line Python pipeline that ingests GitHub issues into Databricks without requiring any configuration or YAML files. The pipeline uses native Databricks support via dlt and REST API integration to extract open issues from GitHub and track updates incrementally. With these improvements, data ingestion into Databricks is now simpler and more efficient, allowing developers to focus on other tasks.

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