<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Vector-Database on Pi Stack</title><link>https://www.pistack.xyz/tags/vector-database/</link><description>Recent content in Vector-Database on Pi Stack</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 12 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.pistack.xyz/tags/vector-database/index.xml" rel="self" type="application/rss+xml"/><item><title>Qdrant vs Milvus vs Weaviate vs Chroma — Best Vector Database 2026</title><link>https://www.pistack.xyz/posts/qdrant-vs-milvus-vs-weaviate-vs-chroma/</link><pubDate>Sun, 12 Apr 2026 00:00:00 +0000</pubDate><guid>https://www.pistack.xyz/posts/qdrant-vs-milvus-vs-weaviate-vs-chroma/</guid><description>&lt;p>Building AI-powered search, retrieval-augmented generation (RAG), or semantic similarity features in 2026 almost always means working with &lt;strong>vector embeddings&lt;/strong> — numerical representations of text, images, or audio. And that means you need a &lt;strong>vector database&lt;/strong>.&lt;/p></description></item></channel></rss>