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Architecture Pattern

CQRS Pattern Visualiser

Watch commands mutate the write model and events sync the read side Animated packet flow · Eventual consistency lag
Command SideWrite model — validates intent, mutates aggregate state, raises domain events
Event BusAsync propagation — events fan out to all registered projections with small lag
Query SideRead model — denormalised, optimised for fast reads. Eventually consistent.
LIVE FLOW
Command
Event
Query
Throughput Stats
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Commands
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Events Published
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Queries
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Projections Updated
Read model lag 0 ms
Event Log

About this demo

This visualiser animates the core CQRS flow: a write model accepts commands, validates them, and appends events to an event store. Each event is published onto an event bus and fanned out to independent projection workers, each maintaining its own optimised read model — whether a search index, an aggregation, or a reporting cache.

The key insight CQRS delivers is that query load never competes with write throughput. Read models can be rebuilt from the event log at any point, and new projections can be added without touching the write path. In high-traffic systems this separation is what allows each side to scale independently.

Pattern: Command Query Responsibility Segregation Technology: Java · Spring Boot · Apache Kafka · MongoDB Read: CQRS with Spring Boot and Kafka →