<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>MicroStream on JAVAPRO International</title><link>https://javapro-en.svenruppert.com/tags/microstream/</link><description>Recent content in MicroStream on JAVAPRO International</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 02 Apr 2026 11:45:01 +0000</lastBuildDate><atom:link href="https://javapro-en.svenruppert.com/tags/microstream/index.xml" rel="self" type="application/rss+xml"/><item><title>Caching and Beyond: Smarter Data Processing with Java - in 2 Hours</title><link>https://javapro-en.svenruppert.com/caching-and-beyond-smarter-data-processing-with-java-in-2-hours/</link><pubDate>Thu, 02 Apr 2026 11:45:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/caching-and-beyond-smarter-data-processing-with-java-in-2-hours/</guid><description>&lt;p&gt;Many Java teams start simple — a single database, a straightforward architecture. But as systems evolve, so does the stack: caching layers to improve performance, search engines for faster queries, additional databases for specialized use cases, and now vector stores for AI-driven features.&lt;/p&gt;
&lt;p&gt;What begins as optimization often turns into a fragmented landscape of technologies. The result: increasing complexity, higher infrastructure costs, and growing DevOps overhead.&lt;/p&gt;
&lt;p&gt;The session &lt;em&gt;“&lt;a href="https://schedule.jcon.one/2026/session/1153509"&gt;Caching and Beyond – Smarter Data Processing with Java&lt;/a&gt;”&lt;/em&gt; at JCON EUROPE takes a different approach. Instead of adding more tools, it focuses on simplifying data architectures — using a clean, Java-centric model built on open-source technologies.&lt;/p&gt;</description></item><item><title>Free Java Training Videos Now Available: From Fundamentals to Modern Frameworks</title><link>https://javapro-en.svenruppert.com/new-java-training-playlists-now-available-from-fundamentals-to-modern-frameworks/</link><pubDate>Wed, 01 Apr 2026 12:00:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/new-java-training-playlists-now-available-from-fundamentals-to-modern-frameworks/</guid><description>&lt;p&gt;A comprehensive collection of Java training videos is now publicly available, offering developers valuable insights into modern backend technologies and frameworks.&lt;/p&gt;
&lt;p&gt;The playlists cover key topics including &lt;strong&gt;Spring Boot, Quarkus, Helidon, Payara, EclipseStore, and MicroStream&lt;/strong&gt;, providing both a strong foundation and deeper technical understanding. The content is designed for developers at all levels—from those starting with modern Java frameworks to experienced engineers looking to refine their expertise.&lt;/p&gt;
&lt;h2 id="structured-learning-across-the-java-ecosystem"&gt;Structured Learning Across the Java Ecosystem&lt;/h2&gt;
&lt;p&gt;Rather than presenting isolated tutorials, the playlists follow a structured approach that helps developers build a coherent understanding of essential concepts such as dependency injection, microservices architecture, data persistence, and performance optimization.&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><item><title>Next Generation Caching &amp; In-Memory Searching</title><link>https://javapro-en.svenruppert.com/next-generation-caching-and-in-memory-searching/</link><pubDate>Mon, 28 Jul 2025 07:00:01 +0000</pubDate><guid>https://javapro-en.svenruppert.com/next-generation-caching-and-in-memory-searching/</guid><description>&lt;h2 id="when-traditional-databases-reach-their-limits"&gt;&lt;strong&gt;When Traditional Databases Reach Their Limits&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Enterprise applications frequently face performance bottlenecks that stem from the underlying persistence layer. Despite decades of database evolution, many core applications still struggle with latency, throughput, and architectural complexity. These issues are particularly evident in systems that depend on complex join operations across multiple tables, need to process unstructured data, or must execute cross-database queries spanning disparate systems to fulfill analytical workflows.&lt;/p&gt;
&lt;p&gt;In such environments, it is common to see a combination of various technologies being deployed in tandem: a traditional relational database, a distributed cache, a NoSQL database, and sometimes a dedicated search server such as Elasticsearch. While each of these systems addresses a specific technical challenge, their co-existence leads to architectural fragmentation, high infrastructure costs, duplicated data models, and increased development and maintenance efforts. Moreover, the overall latency and resource usage often remain suboptimal due to inherent I/O-bound limitations and serialization overheads between systems.&lt;/p&gt;</description></item><item><title>Eclipse Data Grid: The Java-Native In-Memory Data Platform</title><link>https://javapro-en.svenruppert.com/eclipse-data-grid-the-java-native-in-memory-data-platform/</link><pubDate>Thu, 10 Jul 2025 12:00:02 +0000</pubDate><guid>https://javapro-en.svenruppert.com/eclipse-data-grid-the-java-native-in-memory-data-platform/</guid><description>&lt;h2 id="supercharging-java-applications-with-distributed-in-memory-processing"&gt;Supercharging Java Applications with Distributed In-Memory Processing&lt;/h2&gt;
&lt;p&gt;Modern applications increasingly demand low-latency access to complex data. While relational databases remain an indispensable component of most systems, they often struggle to keep up with these performance requirements.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Eclipse Data Grid&lt;/strong&gt; addresses this challenge with a powerful, distributed in-memory data layer designed specifically for Java developers. Rather than serving merely as a cache, Eclipse Data Grid combines high-speed storage, indexing, querying, and transactional persistence—providing a seamless bridge between fast in-memory operations and durable storage.&lt;/p&gt;</description></item><item><title>EclipseStore: The Evolution of Java Persistence</title><link>https://javapro-en.svenruppert.com/eclipsestore-the-evolution-of-java-persistence/</link><pubDate>Mon, 12 May 2025 11:24:29 +0000</pubDate><guid>https://javapro-en.svenruppert.com/eclipsestore-the-evolution-of-java-persistence/</guid><description>&lt;p&gt;Database development in Java has always been a challenge, often feeling like a battle against mismatched paradigms. From the start, developers wrestled with complex mappings and performance bottlenecks when integrating Java with databases. EclipseStore, an open-source project under the Eclipse Foundation, was created to change this. Its mission is to deliver a Java-native persistence layer that feels like an integral part of the language, not a workaround for database limitations. By storing Java objects directly, it aims to simplify and accelerate development, aligning persistence with Java’s core strengths.&lt;/p&gt;</description></item><item><title>Local AI with Java: AI Integration Without Cloud Dependency</title><link>https://javapro-en.svenruppert.com/local-ai-with-java-ai-integration-without-cloud-dependency/</link><pubDate>Fri, 02 May 2025 07:00:03 +0000</pubDate><guid>https://javapro-en.svenruppert.com/local-ai-with-java-ai-integration-without-cloud-dependency/</guid><description>&lt;p&gt;The future of artificial intelligence is local. Increasingly, companies are turning to local AI models to ensure data privacy, offline capabilities, and independence from cloud providers. At &lt;a href="https://2025.europe.jcon.one/"&gt;JCON EUROPE 2025&lt;/a&gt;, the two-hour “&lt;a href="https://schedule.jcon.one/session/894517"&gt;AI-based optimization in expedition planning – a practice-oriented workshop&lt;/a&gt;” with Sven Ruppert will demonstrate exactly how to implement this in Java: high-performance, privacy-friendly AI features – directly in your own application, entirely without cloud services.&lt;/p&gt;
&lt;h2 id="focus-on-the-open-source-project-expedition-planner"&gt;Focus on the Open-Source Project “Expedition Planner”&lt;/h2&gt;
&lt;p&gt;At the center is the open-source project &lt;strong&gt;“Expedition Planner&lt;/strong&gt;”, a Java-based web application designed for planning and organizing expeditions. However, this isn’t just theory: participants will work on real-world use cases, integrating local AI models with &lt;strong&gt;Ollama&lt;/strong&gt;, utilizing &lt;strong&gt;Langchain4j&lt;/strong&gt; and &lt;strong&gt;Retrieval Augmented Generation (RAG)&lt;/strong&gt; to optimize task planning and equipment lists intelligently.&lt;/p&gt;</description></item><item><title>Dynamic Caching for Massive Workloads: Pure Java Solutions First-Hand</title><link>https://javapro-en.svenruppert.com/dynamic-caching-for-massive-workloads-pure-java-solutions-first-hand/</link><pubDate>Tue, 29 Apr 2025 08:54:00 +0000</pubDate><guid>https://javapro-en.svenruppert.com/dynamic-caching-for-massive-workloads-pure-java-solutions-first-hand/</guid><description>&lt;p&gt;Many Java developers encounter the limitations of traditional caching and database solutions when dealing with large amounts of data and dynamically growing workloads. Heavyweight systems often prevent flexible scaling or unnecessarily increase infrastructure costs.&lt;/p&gt;
&lt;p&gt;The session &lt;strong&gt;&amp;quot;&lt;a href="https://schedule.jcon.one/session/851487"&gt;High-Performance Caching with Pure Java – Part 2: Managing Gigantic Workloads&lt;/a&gt;&amp;quot;&lt;/strong&gt; at JCON EUROPE 2025 presents an approach that does things differently: Instead of complex architectures, this approach relies on pure Java – lean, scalable, and powerfull.&lt;/p&gt;</description></item><item><title>Goodbye to ORM Pain: EclipseStore Hands-On with the Lead of the Open-Source Project</title><link>https://javapro-en.svenruppert.com/eclipsestore-hands-on-say-goodbye-to-orm-pain-experience-it-yourself/</link><pubDate>Thu, 24 Apr 2025 12:19:17 +0000</pubDate><guid>https://javapro-en.svenruppert.com/eclipsestore-hands-on-say-goodbye-to-orm-pain-experience-it-yourself/</guid><description>&lt;p&gt;Many Java developers are all too familiar with the downsides of traditional ORM frameworks: performance bottlenecks under scale, complex serialization, and recurring issues when refactoring persistent object models. If you&amp;rsquo;re looking for a modern, high-performance alternative, EclipseStore deserves a closer look – and not just in theory, but in practice.&lt;/p&gt;
&lt;h3 id="experience-eclipsestore-in-action--led-by-a-core-contributor"&gt;&lt;strong&gt;Experience EclipseStore in Action – Led by a Core Contributor&lt;/strong&gt;&lt;/h3&gt;
&lt;p&gt;At this year’s &lt;a href="https://2025.europe.jcon.one/"&gt;JCON EUROPE 2025&lt;/a&gt;, you’ll have a unique opportunity to get hands-on with EclipseStore. &lt;strong&gt;Florian Habermann&lt;/strong&gt;, CTO of MicroStream Software and a core contributor to EclipseStore, is hosting a &lt;a href="https://schedule.jcon.one/session/797351"&gt;&lt;strong&gt;two-hour practical workshop&lt;/strong&gt;&lt;/a&gt;. Rather than sitting through slides, participants will actively code – in their own IDEs, with Java, and against production-relevant use cases.&lt;/p&gt;</description></item><item><title>Minimize Costs by Utilizing Cloud Storage with Spring-Data-Eclipse-Store</title><link>https://javapro-en.svenruppert.com/minimize-costs-by-utilizing-cloud-storage-with-spring-data-eclipse-store/</link><pubDate>Mon, 29 Jul 2024 07:52:28 +0000</pubDate><guid>https://javapro-en.svenruppert.com/minimize-costs-by-utilizing-cloud-storage-with-spring-data-eclipse-store/</guid><description>How to save money storing data in Cloud blob-stores instead of expensive databases through the use of the open-source Spring-Data-Eclipse-Store library.</description></item></channel></rss>