projection-patterns

You build read models from event streams by using projection templates that handle event data and populate queryable data stores like PostgreSQL or Elasticsearch. This Skill provides structured templates for creating live, catchup, persistent, and inline projectors.

The best way to implement CQRS read side projections is to use structured projector patterns that process event streams and populate denormalized materialized views. This Skill provides templates for various data stores to optimize query performance.

Yes, this projection approach works with Elasticsearch and PostgreSQL by providing specific templates for both data stores. You can populate search engines or relational databases based on your event-driven architecture requirements.

You create real-time dashboards by configuring live projections that continuously process event streams and update queryable formats. This ensures your dashboard reflects the latest state by projecting events into optimized read models.

Live projections process events in real-time, catchup projections rebuild read models from historical event streams, and persistent projections maintain state continuously. This Skill implements these patterns to address various event-driven architecture needs.

You should avoid inline projections when query performance optimization requires decoupled processing, as inline projections process events within the write operation. For scalable event-sourced systems, persistent or catchup projections offer better isolation.