event-sourcing

event-sourcing

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Implement event sourcing and CQRS patterns using event stores, aggregates, and projections. Use when building audit trails, temporal queries, or systems requiring full history.

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更新于 2026/3/4
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名称
event-sourcing
描述

Implement event sourcing and CQRS patterns using event stores, aggregates, and projections. Use when building audit trails, temporal queries, or systems requiring full history.

Event Sourcing

Table of Contents

Overview

Store state changes as a sequence of events rather than the current state, enabling temporal queries, audit trails, and event replay.

When to Use

  • Audit trail requirements
  • Temporal queries (state at any point in time)
  • Event-driven microservices
  • CQRS implementations
  • Financial systems
  • Complex domain models
  • Debugging and analysis
  • Compliance and regulation

Quick Start

Minimal working example:

interface DomainEvent {
  id: string;
  aggregateId: string;
  aggregateType: string;
  eventType: string;
  data: any;
  metadata: {
    userId?: string;
    timestamp: number;
    version: number;
  };
}

interface Aggregate {
  id: string;
  version: number;
}

class EventStore {
  private events: DomainEvent[] = [];

  async appendEvents(
    aggregateId: string,
    expectedVersion: number,
    events: Omit<DomainEvent, "id" | "metadata">[],
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
Event Store (TypeScript) Event Store (TypeScript)
Projections (Read Models) Projections (Read Models)
Event Store with PostgreSQL Event Store with PostgreSQL
Snapshots for Performance Snapshots for Performance

Best Practices

✅ DO

  • Store events immutably
  • Version your events
  • Use optimistic concurrency
  • Create snapshots for performance
  • Use projections for queries
  • Keep events small and focused
  • Include metadata (timestamp, user, etc.)
  • Handle event versioning/migration

❌ DON'T

  • Mutate past events
  • Store current state only
  • Skip concurrency checks
  • Query event store for reads
  • Make events too large
  • Forget about event schema evolution