cqrs-implementation

To separate command and query responsibilities, you model state-changing actions as commands processed by command handlers, while serving data retrieval through dedicated query handlers and denormalized read models. This allows independent scaling of read and write paths.

Keeping read models in sync with eventual consistency involves processing domain events through projections. As commands update the write side, projections apply these events to update optimized query views asynchronously, ensuring read stores eventually reflect validated state changes.

You need CQRS and event sourcing when building event-driven systems that require independent read and write paths, scalable reporting, and optimized query performance. It suits services accepting complex user actions while serving fast dashboard queries from separate read stores.

Handling read-your-writes consistency in a CQRS architecture requires specific consistency patterns. Because read models are updated through projections with eventual consistency, you must implement synchronization rules or session-based sticky reads to ensure users see their own updates immediately.

You can use CQRS to optimize performance-sensitive reporting without event sourcing by separating query handlers into dedicated read paths. By maintaining denormalized read models directly updated by command handlers, you achieve scalable reporting without storing full event histories.