先看看示例
作者提供的示例，实际效果取决于你的输入和使用工具。
输入
为订单系统设计事件存储：流 ID 采用 Order-{uuid}，事件从第一天起版本化，并加入 correlation/causation ID 便于追踪。
输出
预期交付：事件存储架构方案、技术选型建议与 schema 设计要点，含流 ID 与版本化约定。（编辑说明，非实际运行结果）
方法说明
---
name: event-store-design
description: Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
---
# Event Store Design
Comprehensive guide to designing event stores for event-sourced applications.
## When to Use This Skill
- Designing event sourcing infrastructure
- Choosing between event store technologies
- Implementing custom event stores
- Optimizing event storage and retrieval
- Setting up event store schemas
- Planning for event store scaling
## Core Concepts
### 1. Event Store Architecture
```
┌─────────────────────────────────────────────────────┐
│ Event Store │
├─────────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Stream 1 │ │ Stream 2 │ │ Stream 3 │ │
│ │ (Aggregate) │ │ (Aggregate) │ │ (Aggregate) │ │
│ ├─────────────┤ ├─────────────┤ ├─────────────┤ │
│ │ Event 1 │ │ Event 1 │ │ Event 1 │ │
│ │ Event 2 │ │ Event 2 │ │ Event 2 │ │
│ │ Event 3 │ │ ... │ │ Event 3 │ │
│ │ ... │ │ │ │ Event 4 │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
├─────────────────────────────────────────────────────┤
│ Global Position: 1 → 2 → 3 → 4 → 5 → 6 → ... │
└─────────────────────────────────────────────────────┘
```
### 2. Event Store Requirements
| Requirement | Description |
| ----------------- | ---------------------------------- |
| **Append-only** | Events are immutable, only appends |
| **Ordered** | Per-stream and global ordering |
| **Versioned** | Optimistic concurrency control |
| **Subscriptions** | Real-time event notifications |
| **Idempotent** | Handle duplicate writes safely |
## Technology Comparison
| Technology | Best For | Limitations |
| ---------------- | ------------------------- | -------------------------------- |
| **EventStoreDB** | Pure event sourcing | Single-purpose |
| **PostgreSQL** | Existing Postgres stack | Manual implementation |
| **Kafka** | High-throughput streaming | Not ideal for per-stream queries |
| **DynamoDB** | Serverless, AWS-native | Query limitations |
| **Marten** | .NET ecosystems | .NET specific |
## 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
- **Use stream IDs that include aggregate type** - `Order-{uuid}`
- **Include correlation/causation IDs** - For tracing
- **Version events from day one** - Plan for schema evolution
- **Implement idempotency** - Use event IDs for deduplication
- **Index appropriately** - For your query patterns
### Don'ts
- **Don't update or delete events** - They're immutable facts
- **Don't store large payloads** - Keep events small
- **Don't skip optimistic concurrency** - Prevents data corruption
- **Don't ignore backpressure** - Handle slow consumers