Command Query Responsibility Segregation separates read and write operations into different models. This enables independent scaling, optimization, and complexity management.
CQRS Basics#
Traditional CRUD:
- Single model for read/write
- Same database for all operations
- Trade-offs between read and write optimization
CQRS:
- Separate models for commands (writes) and queries (reads)
- Optimized data stores for each
- Can scale independently
Simple CQRS Structure#
Loading code block...
Query Side#
Loading code block...
Projections (Updating Read Models)#
Loading code block...
Event Sourcing Integration#
Loading code block...
API Layer#
Loading code block...
Eventual Consistency#
Loading code block...
Best Practices#
When to Use CQRS:
✓ Complex domain logic
✓ Different read/write scaling needs
✓ Multiple read model representations
✓ Audit/history requirements
When to Avoid:
✗ Simple CRUD applications
✗ Small teams/projects
✗ Real-time consistency required
Implementation:
✓ Start simple, add complexity as needed
✓ Handle eventual consistency in UI
✓ Monitor projection lag
✓ Plan for replay scenarios
Conclusion#
CQRS separates concerns and enables independent optimization of reads and writes. Start with simple command/query separation, add event sourcing if you need audit trails, and carefully handle eventual consistency. The complexity is justified when you have different scaling needs or complex domain logic.