<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Redis on wid's blog</title><link>https://wid-blog.github.io/en/tags/redis/</link><description>Recent content in Redis on wid's blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 02 Apr 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://wid-blog.github.io/en/tags/redis/index.xml" rel="self" type="application/rss+xml"/><item><title>MongoDB vs Redis — Same NoSQL, Different Roles</title><link>https://wid-blog.github.io/en/posts/tech/database/mongodb-vs-redis/</link><pubDate>Tue, 02 Apr 2024 00:00:00 +0000</pubDate><guid>https://wid-blog.github.io/en/posts/tech/database/mongodb-vs-redis/</guid><description>Why MongoDB and Redis end up in different roles even under the same NoSQL umbrella. A comparison across data model, storage, schema, scaling, and use cases.</description></item><item><title>Incremental Cache Refresh Pattern</title><link>https://wid-blog.github.io/en/posts/tech/architecture/incremental-cache-refresh/</link><pubDate>Sat, 20 Jan 2024 00:00:00 +0000</pubDate><guid>https://wid-blog.github.io/en/posts/tech/architecture/incremental-cache-refresh/</guid><description>A pattern for switching from full cache refresh to incremental refresh. Separating data by update frequency and applying change detection reduces network costs.</description></item><item><title>Cache Refresh Optimization Retrospective</title><link>https://wid-blog.github.io/en/posts/career/dable/ad-campaign-cache-optimization/</link><pubDate>Mon, 15 Jan 2024 00:00:00 +0000</pubDate><guid>https://wid-blog.github.io/en/posts/career/dable/ad-campaign-cache-optimization/</guid><description>How I reduced network costs and enabled instance downscaling by switching from full cache refresh to incremental refresh for campaign configuration data.</description></item></channel></rss>