What is a projection in event sourcing?

A projection is a process that transforms a stream of events into a specific, structured state or 'read model' that is optimized for querying rather than writing.

How does the skill handle system restarts?

It implements persistent checkpointing, which saves the global position of the last processed event, allowing the projector to resume exactly where it left off.

Can this skill handle historical data migration?

Yes, it includes patterns for 'catch-up' projections specifically designed to process historical event logs to rebuild or update read models from scratch.

Which databases are compatible with these patterns?

While the logic is database-agnostic, the skill provides specific implementation templates for SQL databases like PostgreSQL and search engines like Elasticsearch.

Is this suitable for high-frequency event streams?

Yes, it uses asynchronous processing and batching patterns to efficiently handle high-volume event data without blocking the primary write transaction.

Projection Patterns for Event Sourcing

Name: Projection Patterns for Event Sourcing
Author: duanbiao2000

byduanbiao2000

0•

Database Management

Builds optimized read models and materialized views by projecting event streams into query-efficient databases and search indexes.

This skill provides a comprehensive framework for implementing the read-side of CQRS (Command Query Responsibility Segregation) architectures. It enables developers to transform raw event streams into structured read models, materialized views, and search indexes using standardized patterns for live, catch-up, and persistent projections. By automating the logic for checkpointing and event handling, it helps developers optimize query performance, scale data retrieval, and maintain high-performance dashboards in event-sourced systems.

Key Features

010 GitHub stars

02Automated checkpoint management for resilient data processing

03Implementation patterns for CQRS read-side architectures

04SQL and NoSQL read model templates including PostgreSQL and Elasticsearch

05Real-time data aggregation and search index synchronization logic

06Boilerplate for persistent, catch-up, and live projections

Use Cases

01Building real-time dashboards and reporting tools from microservice event logs

02Generating analytical summaries and daily sales reports from transactional order streams

03Creating high-performance full-text search indexes synchronized with primary event stores

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add duanbiao2000/obsidiandoc26 projection-patterns

For use in Claude.ai and ChatGPT

Download Skill