---
title: Event Store Design
category: product
entity_type: skill
price: $15
canonical: https://forgehouse.ai/skills/event-store-design/
lang: en
hreflang_alt: https://forgehouse.ai/tr/skiller/event-store-design/
last_updated: 2026-06-20
---

# Event Store Design

> Design and implement event stores for event-sourced systems.

A practical guide to designing and implementing event stores for event-sourced systems, where state is kept as an immutable append-only log rather than mutable CRUD rows. It compares EventStoreDB, PostgreSQL, Kafka and DynamoDB, then gives working schemas and implementations so you can pick the right backend and ship it correctly.

## Use cases
- Standing up a PostgreSQL event store with append-only events, snapshots and checkpoints
- Choosing between EventStoreDB, PostgreSQL, Kafka and DynamoDB for your stack
- Implementing optimistic concurrency control to prevent concurrent-write corruption
- Adding snapshots so long streams don't replay from event zero every time
- Building subscriptions that resume from the last processed global position
- Ensuring idempotent writes that safely ignore duplicate events on retry

## Benefits
- Get a complete audit trail and natural undo/redo by treating events as immutable facts
- Prevent data corruption under concurrent load with version-based optimistic concurrency
- Keep read performance high as streams grow by replaying from snapshots instead of the start
- Pick the right event store technology with eyes open to each one's real limitations

## What’s included
- PostgreSQL schema with events, snapshots and subscription_checkpoints tables plus indexes
- Async Python EventStore class with append_events, read_stream, read_all and subscribe
- EventStoreDB client usage including category projections ($ce-)
- DynamoDB single-table event store with partition/sort key design for stream ordering
- Optimistic concurrency, global-position ordering and stream-partitioning patterns
- Snapshot strategy guidance and a do's/don'ts list (never update or delete events)

## Who it’s for
Backend architects and engineers building CQRS or event-sourced systems who need an event store that scales without sacrificing consistency or auditability.

## How it runs
The skill designs the append-only backbone of an event-sourced system end to end. The exact build sequence:
1. Picks the storage technology against a real comparison matrix: EventStoreDB for pure event sourcing, PostgreSQL when the stack already runs Postgres, Kafka for raw throughput, DynamoDB for serverless. Each comes with its known limitation written down.
2. Lays out the schema: an events table with stream_id, event_type, JSONB payload, per-stream version and a global_position BIGSERIAL, locked by a UNIQUE(stream_id, version) constraint. UPDATE and DELETE on events are forbidden, only INSERT.
3. Implements append with optimistic concurrency: every write passes an expected_version, a mismatch raises ConcurrencyError inside the transaction and the client retries with fresh state. Duplicate writes are neutralized by unique event IDs (idempotent write).
4. Provides two read paths: read_stream for rebuilding one aggregate (stream_id plus from_version) and read_all over global_position for cross-stream consumers.
5. Runs subscriptions on checkpoints: each consumer stores its last processed global_position, so a restarted projection resumes exactly where it stopped instead of replaying the world.
6. Adds a snapshot strategy for long streams: persist aggregate state every N events (around 100), load snapshot first, replay only the tail. Stream IDs follow the AggregateType-uuid convention so category-level reads stay possible.

## FAQ
### Can I run this on plain PostgreSQL or do I need a dedicated event database?
Plain PostgreSQL works, and you get a concrete append-only schema with snapshots and checkpoints for it. EventStoreDB, Kafka and DynamoDB are compared so you pick a dedicated store only if your scale demands it.

### Isn't event sourcing overkill compared to normal CRUD?
For plenty of apps it is, and the guide is honest about that rather than pushing it everywhere. It helps you judge when an immutable log actually pays off, like audit-heavy or concurrency-sensitive domains.

### Does it cover the full CQRS read side and projections?
It focuses on the event store itself, the write log, concurrency control and snapshots. Building read models and projections on top is a neighboring concern it sets you up for but does not fully implement.

## Price
$15, one-time, no subscription. VAT included.

Related guide: [AI code review and developer workflow](https://forgehouse.ai/guides/ai-code-review/)