When Does an Entity Stop Being a Data Model?
Most backend applications start simple. You have a few tables, a few endpoints, some business logic, and an ORM or repository layer that keeps persistence manageable. Then the application grows. A Customer is no longer just: id name email Now it also needs: an owner authorization rules validation lifecycle states optimistic concurrency events transactional outbox audit information increasingly…
The article discusses the concept of "entity gravity" in backend applications as they grow in complexity. Initially, entities like a Customer might be simple, but as the application expands, the entity's infrastructure becomes distributed across various components such as controllers, services, repositories, database constraints, and event handlers.
This distribution can lead to challenges when changes to one entity-level rule require coordination with multiple parts of the application. The author proposes a solution by introducing an explicit architectural boundary for the entity, which would handle common mechanics and guarantees. This boundary would allow the application to focus on business decisions while the entity infrastructure manages common mechanics like optimistic concurrency, transactions, and event handling.
The author provides an example of how updates to an entity could be handled with an explicit actor and expected version, ensuring that the transaction records the intent to publish the event, keeping the entity mutation and event recording transactionally consistent.
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