Cqrs Implementation

Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.

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Overview

CQRS Implementation

Comprehensive guide to implementing CQRS (Command Query Responsibility Segregation) patterns.

When to Use This Skill

  • Separating read and write concerns
  • Scaling reads independently from writes
  • Building event-sourced systems
  • Optimizing complex query scenarios
  • Different read/write data models needed
  • High-performance reporting requirements

Core Concepts

1. CQRS Architecture

                    ┌─────────────┐
                    │   Client    │
                    └──────┬──────┘
                           │
              ┌────────────┴────────────┐
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Commands   │          │   Queries   │
       │    API      │          │    API      │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Command    │          │   Query     │
       │  Handlers   │          │  Handlers   │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │   Write     │─────────►│    Read     │
       │   Model     │  Events  │   Model     │
       └─────────────┘          └─────────────┘

2. Key Components

ComponentResponsibility
CommandIntent to change state
Command HandlerValidates and executes commands
EventRecord of state change
QueryRequest for data
Query HandlerRetrieves data from read model
ProjectorUpdates read model from events

Templates and detailed worked examples

Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.

Best Practices

Do's

  • Separate command and query models - Different needs
  • Use eventual consistency - Accept propagation delay
  • Validate in command handlers - Before state change
  • Denormalize read models - Optimize for queries
  • Version your events - For schema evolution

Don'ts

  • Don't query in commands - Use only for writes
  • Don't couple read/write schemas - Independent evolution
  • Don't over-engineer - Start simple
  • Don't ignore consistency SLAs - Define acceptable lag

Best for

  • Separating read and write concerns
  • Scaling reads independently from writes
  • Building event-sourced systems
  • Optimizing complex query scenarios
  • Different read/write data models needed
  • High-performance reporting requirements

Tips and best practices

  • Review the source instructions and adapt inputs before running the workflow.

What This Skill Can Do

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