Event sourcing stores state changes as immutable events rather than current state snapshots. CQRS separates read and write models, enabling independent optimization. Together, these patterns solve specific problems elegantly but add complexity unsuitable for simple domains.
When These Patterns Apply
Event sourcing excels when audit trails matter—financial systems, compliance-heavy domains, and collaborative applications benefit from complete change history. CQRS helps when read and write patterns differ dramatically or when multiple read representations serve different consumers.
- Event sourcing provides complete audit history without additional logging infrastructure
- Temporal queries reconstruct state at any point in history
- CQRS enables read model optimization independent of write model constraints
- Event replay enables bug fixes by reprocessing historical events
- These patterns introduce eventual consistency requiring careful handling
Implementation Challenges
Event schema evolution requires careful versioning strategies. Event stores need efficient snapshotting for aggregates with long event histories. Building and maintaining projections adds operational complexity. Teams should start simple and adopt these patterns only when simpler approaches prove insufficient.