<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SQLite on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/sqlite/</link><description>Recent content in SQLite on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 19 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/sqlite/index.xml" rel="self" type="application/rss+xml"/><item><title>Stoolap vs. SQLite: Complete Technical Comparison 2026</title><link>https://ai-blog.noorshomelab.dev/comparisons/stoolap-vs-sqlite-comparison/</link><pubDate>Thu, 19 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/comparisons/stoolap-vs-sqlite-comparison/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;In the rapidly evolving landscape of embedded databases, developers are constantly seeking solutions that offer the right balance of performance, flexibility, and ease of use. This deep technical comparison, current as of March 19, 2026, pits two prominent contenders against each other: the established and ubiquitous &lt;strong&gt;SQLite&lt;/strong&gt; and the newer, high-performance challenger, &lt;strong&gt;Stoolap&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;SQLite has long been the de-facto standard for embedded, serverless databases, prized for its simplicity, reliability, and compact footprint. However, with modern application demands pushing the boundaries of what embedded databases can achieve, new solutions like Stoolap, built with Rust, are emerging to address high-performance transactional and analytical workloads directly within applications.&lt;/p&gt;</description></item><item><title>Chapter 6: Storing Messages with SQLite</title><link>https://ai-blog.noorshomelab.dev/chat-guide/chapter-6-sqlite-messages/</link><pubDate>Wed, 20 Aug 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/chat-guide/chapter-6-sqlite-messages/</guid><description>&lt;p&gt;A real chat application needs to store messages to provide chat history. This chapter will guide you through setting up a SQLite database and integrating it into our FastAPI application using SQLAlchemy, a powerful SQL toolkit and Object-Relational Mapper (ORM).&lt;/p&gt;
&lt;h3 id="purpose-of-this-chapter"&gt;Purpose of this Chapter&lt;/h3&gt;
&lt;p&gt;By the end of this chapter, you will:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Understand the basics of ORM and why we use SQLAlchemy.&lt;/li&gt;
&lt;li&gt;Set up a SQLite database connection.&lt;/li&gt;
&lt;li&gt;Define database models for users and chat messages.&lt;/li&gt;
&lt;li&gt;Implement methods to store new messages and retrieve chat history.&lt;/li&gt;
&lt;li&gt;Update the WebSocket endpoint to save messages.&lt;/li&gt;
&lt;/ul&gt;
&lt;h3 id="concepts-explained-sqlalchemy-and-orm"&gt;Concepts Explained: SQLAlchemy and ORM&lt;/h3&gt;
&lt;p&gt;&lt;strong&gt;Object-Relational Mapping (ORM)&lt;/strong&gt; is a technique that lets you query and manipulate data from a database using an object-oriented paradigm. Instead of writing raw SQL, you interact with database tables as Python classes and objects.&lt;/p&gt;</description></item></channel></rss>