Event Sourcing vs CQRS: Choosing the Right Pattern for Your Domain

Event Sourcing and CQRS are distinct architectural patterns often used together in complex domains. CQRS separates read and write operations, while Event Sourcing persists state as a sequence of immutable events rather than current state snapshots. Understanding their mechanics and trade-offs is critical for architectural decisions.

What is CQRS?

Command Query Responsibility Segregation (CQRS) splits your system into two separate models:

• Write Model: Handles commands that modify state through Aggregates and enforces business invariants
• Read Model: Handles queries through optimized Projections or denormalized views

The core principle: a method should either change state or return data—never both. This separation enables independent scaling of read and write paths, which is critical when read operations vastly outnumber writes (typical ratio: 100:1 or higher).

What is Event Sourcing

Event Sourcing stores every state change as an immutable event in an append-only Event Store. Instead of persisting the current state, you persist the sequence of events that led to it:

// Traditional CRUD state
{
  "accountId": "123",
  "balance": 500,
  "status": "active"
}

// Event Sourcing representation
[
  {"type": "AccountOpened", "accountId": "123", "timestamp": "2026-01-22T10:00:00Z"},
  {"type": "MoneyDeposited", "accountId": "123", "amount": 500, "timestamp": "2026-01-22T10:05:00Z"}
]

To reconstruct current state, you replay all events for an aggregate in sequence. This provides complete audit trails, temporal queries, and the ability to rebuild projections from scratch.

How They Work Together

CQRS and Event Sourcing complement each other naturally:

1. Command Handler receives a command, validates it against the current aggregate state
2. Aggregate generates one or more domain events
3. Event Store persists events atomically
4. Projectors subscribe to events and update read models asynchronously

// Command Handler
async function handleDeposit(command: DepositCommand) {
  const account = await eventStore.loadEvents(command.accountId);
  const events = account.deposit(command.amount);
  await eventStore.appendEvents(command.accountId, events);
}

// Projector (updates read model)
eventStore.subscribe('MoneyDeposited', async (event) => {
  await readModel.updateBalance(event.accountId, event.amount);
});

The write side focuses on consistency and business rules, while the read side focuses on performance and query optimization.

Technical Trade-offs

Event Sourcing

Advantages:

• Complete audit trail with temporal queries
• Replay events to rebuild state or fix bugs
• Debug by replaying events in development
• Natural fit for event-driven architectures

Disadvantages:

• Event schema versioning complexity
• Event store becomes a bottleneck at scale
• Requires snapshotting for long-lived aggregates
• Eventual consistency between write and read models

CQRS

Advantages:

• Independent scaling of read/write paths
• Optimized data models for each operation type
• Clear separation of concerns
• Better performance for high-read scenarios

Disadvantages:

• Increased architectural complexity
• Eventual consistency challenges
• More code to maintain (two models instead of one)
• Steeper learning curve for teams

When to Use Each Pattern

Use Event Sourcing When:

• Domain requires audit trails (financial, healthcare, logistics)
• Business logic depends on history (approval workflows, state machines)
• You need temporal queries ("what was the state on January 15th?")
• Debugging complex business rules is critical

Use CQRS When:

• Read/write patterns differ significantly
• Query performance is critical and writes are complex
• You need to scale reads independently from writes
• Multiple read models with different shapes are required

Use Both When:

• High-complexity domain with auditing requirements
• Event-driven microservices architecture
• Need for replayable event streams
• Read and write performance requirements diverge

Avoid When:

• Simple CRUD applications suffice
• Team lacks distributed systems experience
• Strong consistency is required everywhere
• Domain doesn't benefit from event history

Getting Started

1. Start with CQRS alone if you only need read/write separation
2. Introduce Event Sourcing for specific aggregates requiring audit trails
3. Implement an Event Store using Kafka, EventStoreDB, or a database append-only table
4. Build projectors to populate read models asynchronously
5. Add snapshotting once aggregates exceed 100-1000 events
6. Monitor projection lag to ensure acceptable read consistency

Begin with a single bounded context rather than applying these patterns across your entire system. The complexity cost is real—only pay it where the domain justifies it.