<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Indexing on Lorbic</title><link>http://localhost:1313/tags/indexing/</link><description>Recent content in Indexing on Lorbic</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 31 Jul 2026 23:00:00 +0530</lastBuildDate><atom:link href="http://localhost:1313/tags/indexing/index.xml" rel="self" type="application/rss+xml"/><item><title>Couchbase Index Best Practices and Query Performance Tuning</title><link>http://localhost:1313/couchbase-index-best-practices-performance-tuning/</link><pubDate>Fri, 31 Jul 2026 23:00:00 +0530</pubDate><guid>http://localhost:1313/couchbase-index-best-practices-performance-tuning/</guid><description>&lt;p>Most Couchbase performance tickets I have seen end the same way: someone adds more nodes, the dashboard looks a little better for a week, and the same query shows up in the slow log a month later. The node count was never the problem. The index was.&lt;/p>
&lt;p>This is a working reference, not an essay. I already wrote &lt;a href="http://localhost:1313/what-couchbase-taught-me-about-system-thinking/">the reflective version&lt;/a> of what indexing in Couchbase teaches you about systems in general. This post skips the reflection and gets straight to the decisions: which index type to reach for, how to order composite keys, how to tell if a query is actually using what you built, and which four or five mistakes account for most of the slow queries you will ever debug. Couchbase&amp;rsquo;s own documentation is the primary source for the recommendations below. Every example runs against &lt;code>travel-sample&lt;/code>, the sample bucket Couchbase ships with every install, so you can paste these into your own cluster and see the plan yourself.&lt;/p></description></item></channel></rss>