Hi ChristianRRL,

Because Community Custom Connectors are backed by Lakeflow pipelines, the compute layer has specific architectural constraints. The underlying pipeline execution framework runs on a custom, managed version of DBR that Databricks continually updates. Properties like DBR aren't generally exposed or user-settable because the platform needs to guarantee compatibility with the ingestion framework, seamlessly apply security patches and ensure consistency across pipeline updates.

Instead of traditional DBR versions, Lakeflow pipelines operate on pipeline environment versions. If you were looking to pin a runtime specifically to control the Python version or pre-installed libraries, you can check if the available environment versions meet your requirements. You can also set the Product Edition (Core/Pro/Advanced) based on your pipeline type.

More details here