Event Sourcing Pipeline
Event-driven architecture for audit trails and state reconstruction
Event Sourcing Architecture
Design an event sourcing pipeline that captures all state changes as a sequence of events.
## Event Sourcing Components
### Core Concepts
- **Event Store**: Immutable append-only log of events
- **Event Streams**: Ordered sequence of related events
- **Aggregates**: Business entities that generate events
- **Projections**: Read models built from event streams
### Data Flow
1. **Command Handling**: Business commands trigger events
2. **Event Generation**: Domain events are created and stored
3. **Event Publishing**: Events are published to subscribers
4. **Projection Building**: Read models are updated from events
### Key Benefits
- **Audit Trail**: Complete history of all changes
- **Temporal Queries**: Query data at any point in time
- **Event Replay**: Rebuild state from historical events
- **Scalability**: Separate read and write concerns
// Event Sourcing Implementation
@Entity
public class CustomerAggregate {
@Id
private String customerId;
@Version
private Long version;
private String name;
private String email;
private CustomerStatus status;
@OneToMany(cascade = CascadeType.ALL, fetch = FetchType.EAGER)
private List<DomainEvent> uncommittedEvents = new ArrayList<>();
public void createCustomer(String name, String email) {
if (this.customerId != null) {
throw new IllegalStateException("Customer already exists");
}
CustomerCreatedEvent event = new CustomerCreatedEvent(
UUID.randomUUID().toString(),
name,
email,
Instant.now()
);
apply(event);
uncommittedEvents.add(event);
}
public void updateEmail(String newEmail) {
if (this.customerId == null) {
throw new IllegalStateException("Customer does not exist");
}
EmailUpdatedEvent event = new EmailUpdatedEvent(
this.customerId,
this.email,
newEmail,
Instant.now()
);
apply(event);
uncommittedEvents.add(event);
}
private void apply(DomainEvent event) {
if (event instanceof CustomerCreatedEvent) {
CustomerCreatedEvent e = (CustomerCreatedEvent) event;
this.customerId = e.getCustomerId();
this.name = e.getName();
this.email = e.getEmail();
this.status = CustomerStatus.ACTIVE;
} else if (event instanceof EmailUpdatedEvent) {
EmailUpdatedEvent e = (EmailUpdatedEvent) event;
this.email = e.getNewEmail();
}
this.version++;
}
public List<DomainEvent> getUncommittedEvents() {
return new ArrayList<>(uncommittedEvents);
}
public void markEventsAsCommitted() {
uncommittedEvents.clear();
}
}
Event Store & Projections
Implement event storage and build read models from event streams.
## Event Storage Strategy
### Event Store Design
- **Event Schema**: Structured event data with metadata
- **Stream Management**: Organize events by aggregate ID
- **Versioning**: Optimistic concurrency control
- **Persistence**: Database or message queue storage
### Projection Building
- **Event Handlers**: Process events to update read models
- **Materialized Views**: Pre-computed query results
- **CQRS Pattern**: Separate command and query models
- **Event Replay**: Rebuild projections from historical events
### Performance Optimization
- **Event Sourcing**: Store only events, not state
- **Snapshot Strategy**: Periodic state snapshots
- **Read Model Caching**: Cache frequently accessed data
- **Event Batching**: Process events in batches
// Event Store Implementation
@Repository
public class EventStore {
@Autowired
private JdbcTemplate jdbcTemplate;
public void appendEvents(String aggregateId, List<DomainEvent> events, long expectedVersion) {
jdbcTemplate.execute(status -> {
// Check version for optimistic concurrency
Long currentVersion = jdbcTemplate.queryForObject(
"SELECT version FROM aggregates WHERE aggregate_id = ?",
Long.class,
aggregateId
);
if (currentVersion != null && currentVersion != expectedVersion) {
throw new ConcurrencyException("Version mismatch");
}
// Insert events
for (DomainEvent event : events) {
jdbcTemplate.update(
"INSERT INTO events (event_id, aggregate_id, event_type, event_data, version, timestamp) VALUES (?, ?, ?, ?, ?, ?)",
event.getEventId(),
aggregateId,
event.getClass().getSimpleName(),
serializeEvent(event),
expectedVersion + 1,
event.getTimestamp()
);
}
// Update aggregate version
if (currentVersion == null) {
jdbcTemplate.update(
"INSERT INTO aggregates (aggregate_id, version) VALUES (?, ?)",
aggregateId,
expectedVersion + events.size()
);
} else {
jdbcTemplate.update(
"UPDATE aggregates SET version = ? WHERE aggregate_id = ?",
expectedVersion + events.size(),
aggregateId
);
}
return null;
});
}
public List<DomainEvent> getEvents(String aggregateId, long fromVersion) {
return jdbcTemplate.query(
"SELECT event_type, event_data, version, timestamp FROM events WHERE aggregate_id = ? AND version > ? ORDER BY version",
new Object[]{aggregateId, fromVersion},
(rs, rowNum) -> deserializeEvent(
rs.getString("event_type"),
rs.getString("event_data"),
rs.getLong("version"),
rs.getTimestamp("timestamp").toInstant()
)
);
}
private String serializeEvent(DomainEvent event) {
try {
ObjectMapper mapper = new ObjectMapper();
return mapper.writeValueAsString(event);
} catch (JsonProcessingException e) {
throw new RuntimeException("Failed to serialize event", e);
}
}
private DomainEvent deserializeEvent(String eventType, String eventData, long version, Instant timestamp) {
try {
ObjectMapper mapper = new ObjectMapper();
Class<?> eventClass = Class.forName("com.example.events." + eventType);
DomainEvent event = (DomainEvent) mapper.readValue(eventData, eventClass);
event.setVersion(version);
event.setTimestamp(timestamp);
return event;
} catch (Exception e) {
throw new RuntimeException("Failed to deserialize event", e);
}
}
}
Implementation Checklist
Event Sourcing Pipeline Implementation Checklist
Follow this comprehensive checklist to ensure successful implementation of your event sourcing pipeline
Event Store Design
Design event storage schema and structure
Aggregate Implementation
Implement domain aggregates with event generation
Event Handlers
Implement event handlers for projection building
Event Replay
Implement event replay for state reconstruction
Architecture Decision Tree
Event Sourcing Architecture Decisions
Decision tree for choosing the right event sourcing architecture
Primary Requirements Assessment
Determine your primary event sourcing requirements
What is your primary requirement?
Technology Stack Comparison
Technology Stack Comparison
Compare different event sourcing technologies
Apache Kafka
streamingDistributed streaming platform for event storage
Key Features
Pros
- Excellent performance
- Large ecosystem
- Production ready
Cons
- Complex setup
- Not purpose-built for event sourcing
Best For
- High-volume event streaming
Not For
- Simple event sourcing
EventStoreDB
databaseEvent sourcing database with built-in event storage
Key Features
Pros
- Purpose-built for event sourcing
- Excellent performance
- Built-in projections
Cons
- Vendor lock-in
- Limited ecosystem
- Steep learning curve
Best For
- Event sourcing applications
Not For
- Traditional CRUD applications
Ready to Build Your Event Sourcing Pipeline?
Start implementing these patterns for event-driven architecture.