Event Store Design
/SKILLComprehensive guide to designing event stores for event-sourced applications.
--- 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