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I think the POV he's taken is that the kafka stream is the one true datasource (for all time), with all other dbs being derivatives. This insane strategy seems to be over engineered to get around db migrations... though i'm sure the event stream will also change over time, and he'll have to write migration-like code anyways.

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There's not just one reason for it.

Kafka lets dependent consumers transform that data into whatever model is appropriate for their use case. There's no one-size-fits-all E-R model for data for all use cases.

It's not just working around db migrations. It's also providing you with the ability to model the data as many ways as you require. How else would you do it, materialized views? How often are they materialized? Regular views? How performant are they?

There are many benefits to this approach, and a lot of them require a different way of thinking. It's a different paradigm.

Isn't that just skinny model, fat client?

If datasource engineers are for some reason implementing "ontogeny recapitulates phylogeny," they won't be creating migration-like code, they'll be writing ETL filters. Break out your Members Only jackets!

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