InfoQ Homepage Java Content on InfoQ
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The Technology Adoption Curve, Twenty Years On
Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years.
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The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It
Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.
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MCP in the Java World: Bringing Architectural Strategy to LLM Integrations
Discover how the Model Context Protocol (MCP) Java SDK is establishing a new architectural discipline for enterprise LLM integrations. By defining explicit contracts and leveraging MCP servers as anti-corruption layers, it ensures governance, loose coupling, and security alignment with the JVM ecosystem and existing operational practices, moving integrations beyond fragility to resilience.
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/articles/redesign-pdf-table-extraction/en/smallimage/redesign-pdf-table-extraction-thumbnail-1776414059821.jpg)
Redesigning Banking PDF Table Extraction: a Layered Approach with Java
PDF table extraction often looks easy until it fails in production. Real bank statements can be messy, with scanned pages, shifting layouts, merged cells, and wrapped rows that break standard Java parsers. This article shares how we redesigned the approach using stream parsing, lattice/OCR, validation, scoring, and selective ML to make extraction more reliable in real banking systems.
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The Spring Team on Spring Framework 7 and Spring Boot 4
InfoQ recently spoke with key members of the Spring team about the significant architectural and functional advancements in Spring Framework 7 and Spring Boot 4. This conversation explores the strategic shift toward core resilience by integrating features such as retry and concurrency throttling directly into the framework, alongside the performance benefits of modularizing auto-configurations.
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Beyond RAG: Architecting Context-Aware AI Systems with Spring Boot
This article introduces Context-Augmented Generation (CAG) as an architectural refinement of RAG for enterprise systems. It shows how a Spring Boot-based context manager can incorporate user identity, session state, and policy constraints into AI workflows, improving traceability, consistency, and governance without altering existing retrievers or LLM infrastructure.
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/articles/kotlin-scalable-swiftui-patterns/en/smallimage/thumbnail-kotlin-scalable-swiftui-patterns-1771922819056.jpg)
Borrowing from Kotlin/Android to Architect Scalable iOS Apps in SwiftUI
Building iOS apps can feel like stitching together guidance from blog posts and Apple samples, which are rarely representative of how production architectures grow and survive. In contrast, the Kotlin/Android ecosystem has converged on well-documented, real-world patterns. This article explores how those approaches can be translated into Swift/SwiftUI to create maintainable, scalable iOS apps.
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Jakarta EE 12 Milestone 2: Advent of the Data Age along with Consistency and Configuration
Jakarta EE 12 Milestone 2 marks the beginning of the next generation of enterprise Java. It introduces Jakarta Query, a unified query language across Persistence, Data, and NoSQL, while aligning the platform with Java 21. This milestone focuses on integration, modernization, and improving developer productivity for cloud-native enterprise applications.
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InfoQ Java Trends Report 2025
This report summarizes how the InfoQ Java editorial team and several Java Champions currently see the adoption of technology and emerging trends within the Java and JVM space in 2025. We focus on Java the language, as well as related languages like Kotlin and Scala, the Java Virtual Machine (JVM), and Java-based frameworks and utilities.
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Building a RAG Application with Spring Boot, Spring AI, MongoDB Atlas Vector Search, and OpenAI
The RAG paradigm redefines AI: it combines generative models and business data for accurate, contextualised responses. The article shows how to integrate Spring Boot, Spring AI, MongoDB Atlas and OpenAI into a powerful and flexible pipeline capable of transforming the way businesses access and create value from data, with applications ranging from finance and healthcare to customer service.
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/articles/onnx-ai-inference-with-java/en/smallimage/Bringing-AI-Inference-to-Java-with-ONNX-thumb-image-1759229686552.jpg)
Bringing AI Inference to Java with ONNX: a Practical Guide for Enterprise Architects
Java applications can now run transformer-based AI models directly within the JVM—without Python, REST wrappers, or microservices. This guide shows how to integrate ONNX-powered inference with tokenizer support, GPU acceleration, modular deployment, and observability, enabling architects in regulated domains to adopt AI without disrupting compliance or CI/CD workflows.
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Evaluating Kotlin Multiplatform: Benefits and Trade-Offs in Cross-Platform Development
KMP is emerging as an alternative for cross-platform development, offering a path to share code without sacrificing the performance and feel of a native application. KMP comes with its own set of trade-offs and this article dives deep into those. While it focuses primarily on Android and iOS, KMP can be used to build desktop, web, and server-side applications, all from the same shared logic.