<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Event Sourcing on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/event-sourcing/</link><description>Recent content in Event Sourcing on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 07 Nov 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/event-sourcing/index.xml" rel="self" type="application/rss+xml"/><item><title>Advanced Topics: Redis Streams for Event Sourcing</title><link>https://ai-blog.noorshomelab.dev/redis-guide/redis-streams/</link><pubDate>Fri, 07 Nov 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/redis-guide/redis-streams/</guid><description>&lt;p&gt;In the &amp;ldquo;Publish/Subscribe&amp;rdquo; chapter, we learned about real-time, fire-and-forget messaging. While powerful for certain use cases, traditional Pub/Sub has a limitation: messages are not persisted. If a subscriber is offline, it misses messages. This is where &lt;strong&gt;Redis Streams&lt;/strong&gt; come in.&lt;/p&gt;
&lt;p&gt;Redis Streams, introduced in Redis 5.0, are a more robust, persistent, and highly scalable messaging solution. They are append-only data structures that act as a continuously growing log, similar in concept to Apache Kafka. Streams are ideal for:&lt;/p&gt;</description></item></channel></rss>