Comparison running dbt-core and dlt-dbt runner on Google Cloud Functions

Running dbt-core or dlt-dbt runner on Google Cloud Functions can simplify data pipeline setup and transformation processes. Two methods are presented: deploying dbt-core, which requires setting up a directory structure and configuring profiles and main.py files, and using the dlt-dbt runner, which automates credential management and simplifies dbt execution within a cloud function. The dlt-dbt runner offers advantages in terms of ease of use and cost-effectiveness, but may not be suitable for resource-intensive pipelines. When choosing between these methods, personal preference plays a role, with some preferring the simplicity of dlt's setup process and others opting for the flexibility of dbt-core. Ultimately, both approaches can be effective for creating lightweight data pipelines on Google Cloud Functions.

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