Patterns

35 items

System Design Pattern

Communicationcqrsread-modelwrite-modelseparationoptimizationadvanced

CQRS Pattern

Separating read and write models for scalability

Used in: E-commerce Catalogs, Reporting Systems, Search|28 min read

Key Takeaways

Asymmetric Read/Write Patterns

Most applications have vastly different read and write patterns. Writes are infrequent and require strong consistency. Reads are frequent and have diverse access patterns. A single model optimized for one pattern compromises the other.

Write Model: Consistency and Rules

The write model focuses on enforcing business invariants, validating commands, and maintaining consistency. It uses normalized schemas and transactions.

Read Model: Speed and Flexibility

Read models are optimized for specific queries. You can have multiple read models: one denormalized for dashboards, one in Elasticsearch for search, one in Redis for real-time updates.

Key Takeaways

Asymmetric Read/Write Patterns

Write Model: Consistency and Rules

The write model focuses on enforcing business invariants, validating commands, and maintaining consistency. It uses normalized schemas and transactions.

Read Model: Speed and Flexibility

Read models are optimized for specific queries. You can have multiple read models: one denormalized for dashboards, one in Elasticsearch for search, one in Redis for real-time updates.

Eventual Consistency Between Models

Write and read models are eventually consistent. When a command updates the write model, read models update asynchronously via events.

Aspect	Advantage	Disadvantage

Patterns

Horizontal Scaling Pattern

Retry with Backoff Pattern

Queue-based Load Leveling Pattern

Replication Pattern

Caching Strategies Pattern

Fan-out Pattern

Fan-in Pattern

Persistent Connections Pattern

Load Balancing Pattern

Circuit Breaker Pattern

Bloom Filters Pattern

Time-Series Storage Pattern

Bulkhead Pattern

Batch Processing Pattern

Write-Ahead Log Pattern

API Gateway Pattern

Backend for Frontend Pattern

Sidecar Pattern

Idempotency Pattern

Rate Limiting Pattern

Backpressure Pattern

Pub/Sub Pattern

Eventual Consistency Pattern

Sharding Pattern

Conflict Resolution Pattern

Strong Consistency Pattern

Leader Election Pattern

Consensus Protocols Pattern

Stream Processing Pattern

Change Data Capture Pattern

Distributed Locking Pattern

Two-Phase Commit Pattern

LSM Trees Pattern

Event Sourcing Pattern

CQRS Pattern

CQRS Pattern

CQRS Pattern

Summary

Key Takeaways

Asymmetric Read/Write Patterns

Write Model: Consistency and Rules

Read Model: Speed and Flexibility

The Problem: One Model for Everything

CQRS Architecture

Premium Content

Natural Fit with Event Sourcing

Pattern Details

The Problem: One Model for Everything

CQRS Architecture

Implementation Example

When to Use CQRS

Trade-offs