CQRS in Practice: When It Helps, When It Hurts, and How We Implement It

CQRS -- separating the write model from the read model -- generates strong opinions. After implementing it in four production systems and deliberately avoiding it in thirty others, our position is clear: it helps in narrow circumstances and hurts in most others.

When CQRS helps: when read and write patterns are fundamentally different. An e-commerce system where writes are individual orders (simple, transactional) but reads are complex dashboard aggregations across thousands of orders. Also when you need the same data projected into multiple read formats -- a logistics client needed shipment data queryable by customer, driver, geography, and time. Four access patterns, each needing different indexes.

When CQRS hurts: when reads and writes are the same shape. A standard CRUD app where users create records and view those records gains nothing from CQRS except a synchronization layer that can get out of sync and the complexity of eventual consistency.

Our pragmatic implementation avoids the full event-sourcing stack. No event stores, event buses, or projection rebuilds. We use PostgreSQL as both write and read database, with materialized views as read models.

The write side is standard service layer with repositories. After each write, a sync function updates relevant materialized views. REFRESH MATERIALIZED VIEW CONCURRENTLY updates without locking reads. For complex projections needing denormalized data, we use database triggers that update read tables in the same transaction, giving strong consistency instead of eventual consistency.

This gives eighty percent of CQRS benefits without the operational complexity of a separate event bus or projection rebuild infrastructure.

The one case where we use full event sourcing: audit-critical financial systems needing complete, immutable state change history. For that, an append-only events table as source of truth with projections building current state from the event stream.

Our recommendation: if your gut says "too complex for my use case," trust it. CQRS is a power tool. Most projects need a screwdriver. Implement it only when you can point to a specific, measurable read/write asymmetry.