Event Sourcing Cheat Sheet

Updated 2026-05-16

Event Sourcing is an architectural pattern where state changes are stored as a sequence of immutable events rather than overwriting current state in a database. Born from Domain-Driven Design and financial ledger systems, this pattern treats events as the single source of truth, allowing complete audit trails and the ability to reconstruct any past state by replaying the event log. Unlike traditional CRUD systems that lose historical context with each update, Event Sourcing preserves every state transition as an append-only log—enabling powerful capabilities like time-travel queries, retroactive corrections, and temporal analysis that are difficult or impossible with conventional persistence. The key mental model is simple: instead of storing where you are, store how you got there—every event is a fact that cannot be changed, only compensated for or refined with new events.

What This Cheat Sheet Covers

This topic spans 12 focused tables and 120 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core ConceptsTable 2: Event Store DesignTable 3: Event Replay and ReconstructionTable 4: Projections and Read ModelsTable 5: CQRS IntegrationTable 5: CQRS IntegrationTable 7: Sagas and CompensationTable 8: Event Store OptimizationTable 9: Production PatternsTable 10: Testing and DebuggingTable 11: Integration and FrameworksTable 12: Advanced Patterns

Table 1: Core Concepts

Concept	Example	Description
Event Store	`events.append(OrderPlaced)` `events.append(OrderShipped)`	• Append-only database that stores every state change as an immutable event • serves as the single source of truth for the system
Aggregate	`class Order:` `def place(self):` `return OrderPlaced(...)`	• Domain entity that enforces business rules and produces events • reconstructed by replaying its event stream • defines the consistency boundary
Event	`OrderPlaced(orderId, customerId, items, timestamp)`	• Immutable record of a past action written in past tense • contains all data needed to describe what happened • the atomic unit of state change
Event Replay	`state = reduce(events, apply, initial)`	• Process of rebuilding aggregate state from scratch by sequentially applying all historical events • enables time-travel and state reconstruction
Projection	`def on_OrderPlaced(event):` `db.orders.insert(...)`	• Read model built by processing events to answer specific queries • typically eventual consistent • optimized for read performance not writes

Table 1: Core Concepts

Concept	Example	Description
Event Store	`events.append(OrderPlaced)` `events.append(OrderShipped)`	• Append-only database that stores every state change as an immutable event • serves as the single source of truth for the system
Aggregate	`class Order:` `def place(self):` `return OrderPlaced(...)`	• Domain entity that enforces business rules and produces events • reconstructed by replaying its event stream • defines the consistency boundary
Event	`OrderPlaced(orderId, customerId, items, timestamp)`	• Immutable record of a past action written in past tense • contains all data needed to describe what happened • the atomic unit of state change
Event Replay	`state = reduce(events, apply, initial)`	• Process of rebuilding aggregate state from scratch by sequentially applying all historical events • enables time-travel and state reconstruction
Projection	`def on_OrderPlaced(event):` `db.orders.insert(...)`	• Read model built by processing events to answer specific queries • typically eventual consistent • optimized for read performance not writes