projection-patterns

You can build read models from event streams by applying transformations to event types, such as OrderCreated, to update materialized views or database tables for optimized query performance. This Skill facilitates creating those CQRS read sides.

Optimizing query performance in event-sourced systems involves creating projections that pre-calculate and store aggregated data. This Skill generates denormalized materialized views from event streams, enabling faster querying without replaying the entire event log.

Available projection patterns for processing event streams include live, catchup, and persistent projections. These patterns handle event types and apply transformations to update read models, accommodating various data consistency and synchronization requirements.

Yes, you can maintain real-time summary tables for dashboards by processing events like OrderCreated and OrderCompleted. This Skill applies transformations to update read models, keeping aggregated dashboard data up-to-date through live projections.

Creating materialized views from event streams often involves database interactions or search index updates to store the read models. You need a destination data store to persist the denormalized views generated by the projection transformations.

You should avoid using projections when your system cannot handle eventual consistency between the event stream and the read model. Building read models requires applying transformations to events, meaning the materialized views may lag behind the source event stream.