Summary

In this chapter, you learned why data gravity impedes innovation and how to decompose monolithic databases throughout the phases of the data life cycle. You learned how the CQRS pattern turns the database inside out and ultimately turns the cloud into the database by creating a system-wide transaction log and moving derived data downstream to where it is used. You also learned how to increase team confidence by using materialized views to create inbound bulkheads.

We dug into the details and you learned how to create stream processors that are idempotent and order tolerant, and you saw how to keep data lean. You also learned about using the Single Table Design modeling technique to optimize data for performance and how to create stream processors that leverage change data capture to implement the database-first variant of the event sourcing pattern.

In the next chapter, we will cover the BFF pattern and see how it unencumbers teams by removing competing demands so...