What are projection patterns?

Projection patterns are architectural methods used to transform a stream of events into a specific data format, known as a read model, which is optimized for specific query requirements.

Does this skill support different database types?

Yes, the skill provides templates for relational databases using SQL, document stores like Elasticsearch, and general aggregation logic that can be adapted to any storage engine.

When should I use this Claude Code skill?

Use this skill when building event-sourced systems where you need to create fast query interfaces, real-time dashboards, or search indexes that stay in sync with your primary event log.

How does it handle data consistency during a restart?

It implements persistent projections and checkpointing, ensuring the projector remembers its last processed event position so it can resume accurately without data loss or duplication.

Projection Patterns for Event Sourcing

Name: Projection Patterns for Event Sourcing
Author: Microck

byMicrock

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Database Management

Builds high-performance read models and materialized views from event streams using standardized architectural patterns.

This skill provides a comprehensive framework for implementing Command Query Responsibility Segregation (CQRS) read sides within event-driven architectures. It offers battle-tested templates for building live, catchup, and persistent projections that transform raw event logs into optimized queryable formats like SQL tables, Elasticsearch indexes, or real-time dashboards. By decoupling the write model from the read model, it enables developers to scale query performance independently, support complex full-text search, and generate sophisticated data aggregations without impacting the primary transactional system.

Key Features

01Robust checkpointing mechanisms for data consistency and resume-ability

02Templates for SQL-based order summaries and data aggregation

03Support for Live, Catchup, and Persistent projection types

042 GitHub stars

05Elasticsearch integration for full-text search indexing

06Standardized projection architecture for CQRS read sides

Use Cases

01Aggregating transactional data into daily or monthly analytical sales reports

02Creating high-performance materialized views for complex real-time dashboards

03Building searchable product catalogs from distributed event streams

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/opendots-microck projection-patterns

For use in Claude.ai and ChatGPT

Download Skill