event-store-design
The event-store-design skill provides comprehensive guidance for architecting event stores in event-sourced systems, covering core concepts like stream organization and global event ordering, technology selection across platforms including EventStoreDB and PostgreSQL, and implementation requirements such as append-only persistence and idempotent writes. Use this skill when designing event sourcing infrastructure, evaluating event store technologies, implementing custom persistence layers, or planning for scalability in event-driven applications.
git clone --depth 1 https://github.com/wshobson/agents /tmp/event-store-design && cp -r /tmp/event-store-design/plugins/backend-development/skills/event-store-design ~/.claude/skills/event-store-designSKILL.md
# 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 consumersBuild production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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