event-store-design
設計 event sourcing 用的 event store：技術比較、需求和最佳實務
中文翻譯
---
name: event-store-design
description: 為 event-sourced 系統設計並實作 event store。適用於建構 event sourcing 基礎設施、選擇 event store 技術，或實作事件持久化模式的時候。
---
# Event Store 設計
為 event sourcing 應用設計 event store 的完整指南。
## 什麼時候用這個 Skill
- 設計 event sourcing 基礎設施
- 在不同的 event store 技術之間做選擇
- 實作自訂的 event store
- 最佳化事件的儲存與讀取
- 設定 event store 的 schema
- 規劃 event store 的擴充
## 核心概念
### 1. Event Store 架構
```
┌─────────────────────────────────────────────────────┐
│ 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 需求
| 需求 | 說明 |
| ----------------- | ---------------------------------- |
| **Append-only** | 事件不可變，只能附加 |
| **有順序** | 每個 stream 以及全域都有順序 |
| **有版本** | 樂觀並行控制 |
| **訂閱** | 即時事件通知 |
| **Idempotent** | 安全地處理重複寫入 |
## 技術比較
| 技術 | 最適合 | 限制 |
| ---------------- | ------------------------- | -------------------------------- |
| **EventStoreDB** | 純 event sourcing | 用途單一 |
| **PostgreSQL** | 已有 Postgres 技術棧 | 需要手動實作 |
| **Kafka** | 高吞吐量的串流 | 不適合以 stream 為單位的查詢 |
| **DynamoDB** | Serverless、AWS 原生 | 查詢能力有限 |
| **Marten** | .NET 生態系 | 僅限 .NET |
## 範本與詳細實作範例
完整的範本庫和詳細實作範例放在 `references/details.md`，需要具體範本的時候去讀那份檔案。
## 最佳實務
### 該做的
- **stream ID 要包含 aggregate 類型**：`Order-{uuid}`
- **包含 correlation/causation ID**：方便追蹤
- **從第一天就為事件加版本**：為 schema 演進做準備
- **實作 idempotency**：用事件 ID 做去重
- **適當建立索引**：依你的查詢模式
### 不該做的
- **不要更新或刪除事件**：它們是不可變的事實
- **不要存大型的 payload**：事件要保持精簡
- **不要跳過樂觀並行控制**：它能防止資料毀損
- **不要忽略 backpressure**：要處理消費速度慢的 consumer英文原文
---
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