projection-patterns

You build read models from event streams by organizing an event store, projector, and read model into a pipeline. This creates fast query paths for CQRS dashboards without scanning raw events, using idempotent projection handlers and checkpointed replay to ensure data consistency.

Projection types in event sourcing include live, catchup, persistent, and inline projections. You choose between them based on your specific latency, consistency, and recovery needs, allowing you to balance real-time updates with safe rebuild workflows for materialized views.

Idempotent projection handlers are ensured by using checkpointed replay and transactional multi-table updates. This event sourcing mechanism tracks processed events safely, preventing duplicate data updates when rebuilding read models or replaying domain event streams.

Yes, event sourcing projections support building search indexes, aggregate reports, and multi-table summaries from domain events. You apply projection patterns to transform raw event streams into optimized materialized views for fast querying and reporting.

You need checkpointed replay for materialized views when recovering from failures or rebuilding read models in an event-sourced system. Checkpointing tracks the last processed event, allowing projection handlers to resume safely without reprocessing the entire event stream history.