What are projections in event sourcing?

Projections are processes that transform a stream of events into a specific data format (a read model) that is highly optimized for querying and display.

When should I use the projection-patterns skill?

Use it when implementing CQRS architecture, building materialized views, or when you need to optimize search and dashboard performance in event-driven systems.

Does this skill support real-time updates?

Yes, it includes patterns for live projections that subscribe to event stores and update read models immediately as events occur.

Can I rebuild my data if the read model schema changes?

Absolutely. The skill provides 'Catchup' and 'Rebuild' patterns designed to re-process historical events into updated read model schemas from scratch.

Projection Patterns

Name: Projection Patterns
Author: wshobson

bywshobson

•

23,194

데이터베이스 관리

Builds high-performance read models and materialized views from event streams for event-sourced architectures.

소개

This skill provides specialized guidance and templates for implementing the read side of Command Query Responsibility Segregation (CQRS) and event-sourced systems. It enables developers to transform raw event streams into optimized query models, manage checkpoints for persistent processing, and handle complex data aggregations. Whether you are building real-time dashboards, full-text search indexes in Elasticsearch, or SQL-based summary tables, this skill offers robust implementation patterns for keeping your read models consistent, performant, and resilient.

주요 기능

Checkpoint management for resilient and resumable event processing
Complex event aggregation and multi-table update patterns
Standardized projection architecture for CQRS read models
Support for Live, Catchup, Persistent, and Inline projection types
Pre-built templates for SQL summaries and Elasticsearch indexing
23,194 GitHub stars

사용 사례

Syncing event-driven data with search engines like Elasticsearch
Building optimized read models from an event-sourced backend
Creating real-time analytical dashboards from stream data

소개

주요 기능

Checkpoint management for resilient and resumable event processing
Complex event aggregation and multi-table update patterns
Standardized projection architecture for CQRS read models
Support for Live, Catchup, Persistent, and Inline projection types
Pre-built templates for SQL summaries and Elasticsearch indexing
23,194 GitHub stars

사용 사례

Syncing event-driven data with search engines like Elasticsearch
Building optimized read models from an event-sourced backend
Creating real-time analytical dashboards from stream data