This is a companion discussion topic for the original entry at dbt Squared: Leveraging dbt Core and dbt Cloud together at scale | dbt Developer Blog
Thank you for giving this overview for scaling up dbt Core to dbt Cloud - it is a helpful use case to explore. I am new to dbt myself, but the teams I work with are looking at something similar where we have off-shore teams contributing to a common data model. However, in our current structure we have the “opposite” layout - the base team uses dbt Cloud, and we would like the additional contributing teams to use dbt Core.
It sounds like in this scenario, the “core” team was the only group contributing to the common base data model, and then the international teams built their own models downstream, on top of this, for custom metrics/analytics. Is my understanding correct? If yes, is there any functionality where a team using dbt Core could contribute to the same models as a team using dbt Cloud? In other words, can the two system contribute to the same project and datasets? Or is the splitting of projects the recommended architecture? Can the separate projects contribute to the same data models? Is there a risk of the models falling out of sync, in this case? Any insights from your experience is appreciated.