My main use case for Coalesce.io was with a healthcare provider client whose team was not particularly tech savvy, so we wanted something easy to use. I was debating between two options: Coalesce.io and DBT. Coalesce.io had a GUI interface where I could drag and drop objects and build easily, so I was exploring it for building data vault models.
For that specific use case, I was able to accomplish what I was trying to do during the demo, but we encountered certain scenarios such as post-hooks, update statements, edge cases, or particular SQL query modifications and custom cases that could not be implemented through the GUI interface. Additionally, jobs that were interdependent on each other and orchestration features were not available at that time, which made us reconsider our options and ultimately go with DBT since it was open source and DBT Cloud had all the features we wanted.
I used Coalesce.io to build a data vault model by reaching out to the Coalesce.io team when the initial account provided to us did not have access to packages used for data vault modeling. They enabled a package specific for data vault modeling within the account. In that specific scenario, we wanted to replicate or build a small demo for the client to show them how we could leverage Coalesce.io to build data vault models. In data vault, we have a use case of needing to build multiple objects for creating dimensions and facts with an intermediate layer of hubs, links, and satellites. We used the package provided by the Coalesce.io team, which streamlined the process of creating these objects and provided a template that had all these columns in a particular format. We only needed to enter the column names and drag and drop to create our final model, which was very convenient. However, there were some problems and nuances due to which we went with DBT.
