Event Store Design
Seth HobsonCommunityCreated by Seth Hobson
- Skill
- Guidelines
- Software development
- MIT
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured approach to designing event stores, covering core architectural requirements, technology comparisons, and implementation best practices. It emphasizes the immutable, append-only nature of event sourcing and provides concrete templates for schema design and application-level implementation to ensure data integrity, concurrency control, and efficient event retrieval.
What it does
- Defines core requirements for event stores including immutability and optimistic concurrency.
- Compares common storage technologies like PostgreSQL, Kafka, and DynamoDB for event sourcing.
- Provides SQL schema templates for event and snapshot storage.
- Offers implementation patterns for appending events with version checking.
- Outlines best practices for stream naming, event metadata, and schema evolution.
- Details strategies for handling idempotency and subscription checkpoints.
When to use it
- When architecting the persistence layer for an event-sourced system.
- When evaluating which database technology best fits your event sourcing needs.
- When implementing custom event store logic in a backend application.
- When optimizing event storage schemas for performance and scalability.
- When establishing patterns for event versioning and schema evolution.
Advantages
- Ensures data consistency through optimistic concurrency control.
- Provides a clear framework for choosing the right storage technology.
- Includes ready-to-use SQL and code templates for rapid implementation.
- Promotes best practices for long-term system maintainability and tracing.
- Addresses critical operational concerns like idempotency and backpressure.
Usage examples
- “How should I structure my PostgreSQL schema for an event store?”
- The agent provides a SQL template including tables for events, snapshots, and subscription checkpoints with appropriate indexing.
- “What are the pros and cons of using Kafka versus PostgreSQL for event sourcing?”
- The agent compares the two, highlighting Kafka's high-throughput streaming capabilities versus PostgreSQL's suitability for per-stream queries.
- “How do I implement optimistic concurrency when appending events?”
- The agent explains the version-checking pattern and provides a Python code example using a database transaction.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/wshobson/event-store-design/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip event-store-design.zip -d .agents/skills
Documentation by Seth Hobson
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
Files
- ATTRIBUTION.mdAdded by AutoGineer992 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md4.1 KiB
- references/details.md11.2 KiB
references/details.md
event-store-design — templates and worked examples
Templates
Template 1: PostgreSQL Event Store Schema
-- Events table
CREATE TABLE events (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
stream_id VARCHAR(255) NOT NULL,
stream_type VARCHAR(255) NOT NULL,
event_type VARCHAR(255) NOT NULL,
event_data JSONB NOT NULL,
metadata JSONB DEFAULT '{}',
version BIGINT NOT NULL,
global_position BIGSERIAL,
created_at TIMESTAMPTZ DEFAULT NOW(),
CONSTRAINT unique_stream_version UNIQUE (stream_id, version)
);
-- Index for stream queries
CREATE INDEX idx_events_stream_id ON events(stream_id, version);
-- Index for global subscription
CREATE INDEX idx_events_global_position ON events(global_position);
-- Index for event type queries
CREATE INDEX idx_events_event_type ON events(event_type);
-- Index for time-based queries
CREATE INDEX idx_events_created_at ON events(created_at);
-- Snapshots table
CREATE TABLE snapshots (
stream_id VARCHAR(255) PRIMARY KEY,
stream_type VARCHAR(255) NOT NULL,
snapshot_data JSONB NOT NULL,
version BIGINT NOT NULL,
created_at TIMESTAMPTZ DEFAULT NOW()
);
-- Subscriptions checkpoint table
CREATE TABLE subscription_checkpoints (
subscription_id VARCHAR(255) PRIMARY KEY,
last_position BIGINT NOT NULL DEFAULT 0,
updated_at TIMESTAMPTZ DEFAULT NOW()
);Template 2: Python Event Store Implementation
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Optional, List
from uuid import UUID, uuid4
import json
import asyncpg
@dataclass
class Event:
stream_id: str
event_type: str
data: dict
metadata: dict = field(default_factory=dict)
event_id: UUID = field(default_factory=uuid4)
version: Optional[int] = None
global_position: Optional[int] = None
created_at: datetime = field(default_factory=datetime.utcnow)
class EventStore:
def __init__(self, pool: asyncpg.Pool):
self.pool = pool
async def append_events(
self,
stream_id: str,
stream_type: str,
events: List[Event],
expected_version: Optional[int] = None
) -> List[Event]:
"""Append events to a stream with optimistic concurrency."""
async with self.pool.acquire() as conn:
async with conn.transaction():
# Check expected version
if expected_version is not None:
current = await conn.fetchval(
"SELECT MAX(version) FROM events WHERE stream_id = $1",
stream_id
)
current = current or 0
if current != expected_version:
raise ConcurrencyError(
f"Expected version {expected_version}, got {current}"
)
# Get starting version
start_version = await conn.fetchval(
"SELECT COALESCE(MAX(version), 0) + 1 FROM events WHERE stream_id = $1",
stream_id
)
# Insert events
saved_events = []
for i, event in enumerate(events):
event.version = start_version + i
row = await conn.fetchrow(
"""
INSERT INTO events (id, stream_id, stream_type, event_type,
event_data, metadata, version, created_at)
VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
RETURNING global_position
""",
event.event_id,
stream_id,
stream_type,
event.event_type,
json.dumps(event.data),
json.dumps(event.metadata),
event.version,
event.created_at
)
event.global_position = row['global_position']
saved_events.append(event)
return saved_events
async def read_stream(
self,
stream_id: str,
from_version: int = 0,
limit: int = 1000
) -> List[Event]:
"""Read events from a stream."""
async with self.pool.acquire() as conn:
rows = await conn.fetch(
"""
SELECT id, stream_id, event_type, event_data, metadata,
version, global_position, created_at
FROM events
WHERE stream_id = $1 AND version >= $2
ORDER BY version
LIMIT $3
""",
stream_id, from_version, limit
)
return [self._row_to_event(row) for row in rows]
async def read_all(
self,
from_position: int = 0,
limit: int = 1000
) -> List[Event]:
"""Read all events globally."""
async with self.pool.acquire() as conn:
rows = await conn.fetch(
"""
SELECT id, stream_id, event_type, event_data, metadata,
version, global_position, created_at
FROM events
WHERE global_position > $1
ORDER BY global_position
LIMIT $2
""",
from_position, limit
)
return [self._row_to_event(row) for row in rows]
async def subscribe(
self,
subscription_id: str,
handler,
from_position: int = 0,
batch_size: int = 100
):
"""Subscribe to all events from a position."""
# Get checkpoint
async with self.pool.acquire() as conn:
checkpoint = await conn.fetchval(
"""
SELECT last_position FROM subscription_checkpoints
WHERE subscription_id = $1
""",
subscription_id
)
position = checkpoint or from_position
while True:
events = await self.read_all(position, batch_size)
if not events:
await asyncio.sleep(1) # Poll interval
continue
for event in events:
await handler(event)
position = event.global_position
# Save checkpoint
async with self.pool.acquire() as conn:
await conn.execute(
"""
INSERT INTO subscription_checkpoints (subscription_id, last_position)
VALUES ($1, $2)
ON CONFLICT (subscription_id)
DO UPDATE SET last_position = $2, updated_at = NOW()
""",
subscription_id, position
)
def _row_to_event(self, row) -> Event:
return Event(
event_id=row['id'],
stream_id=row['stream_id'],
event_type=row['event_type'],
data=json.loads(row['event_data']),
metadata=json.loads(row['metadata']),
version=row['version'],
global_position=row['global_position'],
created_at=row['created_at']
)
class ConcurrencyError(Exception):
"""Raised when optimistic concurrency check fails."""
passTemplate 3: EventStoreDB Usage
from esdbclient import EventStoreDBClient, NewEvent, StreamState
import json
# Connect
client = EventStoreDBClient(uri="esdb://localhost:2113?tls=false")
# Append events
def append_events(stream_name: str, events: list, expected_revision=None):
new_events = [
NewEvent(
type=event['type'],
data=json.dumps(event['data']).encode(),
metadata=json.dumps(event.get('metadata', {})).encode()
)
for event in events
]
if expected_revision is None:
state = StreamState.ANY
elif expected_revision == -1:
state = StreamState.NO_STREAM
else:
state = expected_revision
return client.append_to_stream(
stream_name=stream_name,
events=new_events,
current_version=state
)
# Read stream
def read_stream(stream_name: str, from_revision: int = 0):
events = client.get_stream(
stream_name=stream_name,
stream_position=from_revision
)
return [
{
'type': event.type,
'data': json.loads(event.data),
'metadata': json.loads(event.metadata) if event.metadata else {},
'stream_position': event.stream_position,
'commit_position': event.commit_position
}
for event in events
]
# Subscribe to all
async def subscribe_to_all(handler, from_position: int = 0):
subscription = client.subscribe_to_all(commit_position=from_position)
async for event in subscription:
await handler({
'type': event.type,
'data': json.loads(event.data),
'stream_id': event.stream_name,
'position': event.commit_position
})
# Category projection ($ce-Category)
def read_category(category: str):
"""Read all events for a category using system projection."""
return read_stream(f"$ce-{category}")Template 4: DynamoDB Event Store
import boto3
from boto3.dynamodb.conditions import Key
from datetime import datetime
import json
import uuid
class DynamoEventStore:
def __init__(self, table_name: str):
self.dynamodb = boto3.resource('dynamodb')
self.table = self.dynamodb.Table(table_name)
def append_events(self, stream_id: str, events: list, expected_version: int = None):
"""Append events with conditional write for concurrency."""
with self.table.batch_writer() as batch:
for i, event in enumerate(events):
version = (expected_version or 0) + i + 1
item = {
'PK': f"STREAM#{stream_id}",
'SK': f"VERSION#{version:020d}",
'GSI1PK': 'EVENTS',
'GSI1SK': datetime.utcnow().isoformat(),
'event_id': str(uuid.uuid4()),
'stream_id': stream_id,
'event_type': event['type'],
'event_data': json.dumps(event['data']),
'version': version,
'created_at': datetime.utcnow().isoformat()
}
batch.put_item(Item=item)
return events
def read_stream(self, stream_id: str, from_version: int = 0):
"""Read events from a stream."""
response = self.table.query(
KeyConditionExpression=Key('PK').eq(f"STREAM#{stream_id}") &
Key('SK').gte(f"VERSION#{from_version:020d}")
)
return [
{
'event_type': item['event_type'],
'data': json.loads(item['event_data']),
'version': item['version']
}
for item in response['Items']
]
# Table definition (CloudFormation/Terraform)
"""
DynamoDB Table:
- PK (Partition Key): String
- SK (Sort Key): String
- GSI1PK, GSI1SK for global ordering
Capacity: On-demand or provisioned based on throughput needs
"""Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
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Attribution and licence
- Created by
- Seth Hobson
- Publisher
- Seth Hobson (Community)
- Source
- wshobson/agents · plugins/backend-development/skills/event-store-design · commit 4bde316
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Seth Hobson or Seth Hobson.
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