<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Embeddings on JAVAPRO International</title><link>https://javapro-en.svenruppert.com/tags/embeddings/</link><description>Recent content in Embeddings on JAVAPRO International</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 02 Apr 2026 07:00:01 +0000</lastBuildDate><atom:link href="https://javapro-en.svenruppert.com/tags/embeddings/index.xml" rel="self" type="application/rss+xml"/><item><title>Build Vector Database Apps with Pure Java</title><link>https://javapro-en.svenruppert.com/build-vector-database-apps-with-pure-java/</link><pubDate>Thu, 02 Apr 2026 07:00:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/build-vector-database-apps-with-pure-java/</guid><description>&lt;p&gt;&lt;a href="https://youtu.be/MRSdUfnXgQE"&gt;&lt;figure class="post-figure"&gt;
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&lt;p&gt;The Java ecosystem is entering a new phase. Generative AI is no longer experimental; it is becoming a foundational capability in enterprise systems. Yet while frameworks for inference and orchestration have matured, one critical bottleneck continues to slow down adoption: data access for semantic retrieval.&lt;/p&gt;
&lt;p&gt;At the heart of modern GenAI systems lies Retrieval-Augmented Generation (RAG). This paradigm depends on fast access to embeddings - high-dimensional vectors that represent meaning. For Java developers, integrating this capability has historically meant introducing an external vector database into the architecture. What appears to be a straightforward design decision quickly becomes a source of complexity, inefficiency, and architectural friction.&lt;/p&gt;</description></item><item><title>EclipseStore 4.0.0 Beta 1: Build Java vector database Apps</title><link>https://javapro-en.svenruppert.com/eclipsestore-4-0-0-beta-1-build-java-vector-database-apps/</link><pubDate>Mon, 16 Feb 2026 12:19:02 +0000</pubDate><guid>https://javapro-en.svenruppert.com/eclipsestore-4-0-0-beta-1-build-java-vector-database-apps/</guid><description>&lt;p&gt;The first beta of &lt;strong&gt;EclipseStore 4.0.0&lt;/strong&gt; is now available, marking a major evolution of the Java-nativ persistence engine. With this version, EclipseStore has integrated the high-performance vector similarity search engine JVector and therefore becomes an embedded Java vector database engine that runs within the same JVM process as your GenAI app. With EclipseStore 4, Java developers can now build powerful GenAI apps with pure Java, without the need to use external vector databases. This makes the entire development process of GenAI apps very convenient and significantly faster, simplifying testing and deployment.&lt;/p&gt;</description></item></channel></rss>