Browsing Tag

kafka

225 posts
The Ultimate Data Streaming Guide - Book and Industry Editions Manufacturing Automotive Financial Services Telecom Media Digital Natives
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The Ultimate Data Streaming Guide is Back – Second Edition of the Book and Industry Editions Now Available

The second edition of The Ultimate Data Streaming Guide is now available as a free eBook. It includes over 70 use cases, over 20 customer stories, a detailed use case / customer matrix, and a stronger focus on AI topics like GenAI and Agentic AI. The book shows how organizations use Apache Kafka, Apache Flink, and the Confluent Data Streaming Platform to build real-time solutions with business impact. New Industry Editions are also available for Financial Services, Manufacturing and Automotive, Telecom and Media, and Digital Natives.
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Introduction Queues for Kafka - Apache Kafka QfK - One Platform for Event Streaming and Message Queues Consolidation
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When (Not) to Use Queues for Kafka?

Apache Kafka has long been the foundation for real-time data streaming. With the release of Queues for Kafka (QfK) in Apache Kafka 4.2, it now also supports native queuing, eliminating the need for separate message queue systems for backend integration and task processing. This blog explores how Kafka bridges the gap between stream processing and message queuing, when (not) to use QfK, and how it enables a unified cloud-native integration platform for modern enterprise architectures.
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Real Time Airline Operations at Etihad Airways with Data Streaming Using Apache Kafka and Flink
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Etihad Airways Makes Airline Operations Real-Time with Data Streaming

Airlines face constant pressure to deliver reliable service while managing complex operations and rising customer expectations. This blog post explores how Etihad Airways uses real-time data streaming with Apache Kafka and Flink to improve operational efficiency and passenger experience. Based on a presentation at the Data Streaming World Tour in Dubai, it highlights how Etihad built an event-driven platform to move from delayed insights to real-time action. The post also connects this story to other data streaming success cases in the aviation industry, including Lufthansa , Cathay Pacific, Virgin Australia, and Schiphol Airport in Amsterdam.
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10 FinTech Predictions That Depend On Real Time Data Streaming
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10 FinTech Predictions That Depend on Real Time Data Streaming

Financial services companies are moving from batch processing to real time data flow. A data streaming platform enables financial institutions to connect systems, process events instantly, and power AI, fraud prevention, and customer engagement. This post explores ten FinTech trends and shows how real time data unlocks business value across the industry.
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Data Streaming Trends for 2026 with Apache Kafka Flink Diskless Cloud Agentic AI
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Top Trends for Data Streaming with Apache Kafka and Flink in 2026

Each year brings new momentum to the data streaming space. In 2026, six key trends stand out. Platforms and vendors are consolidating. Diskless Kafka and Apache Iceberg are reshaping storage. Real-time analytics is moving into the stream. Enterprises demand zero data loss and regional compliance. Streaming is now powering operational AI with real-time context. Data streaming has evolved. It is now strategic infrastructure at the heart of modern enterprise systems.
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The Data Streaming Landscape 2026

Data streaming is now a core software category in modern data architecture. It powers real-time use cases like fraud prevention, personalization, supply chain optimization, and AI automation. What started with open source Apache Kafka and Flink has grown into a critical layer for business operations. The 2026 Data Streaming Landscape shows the most relevant Data Streaming Platform evolution. These platforms connect systems, process data in motion, enforce governance, and support mission-critical workloads at scale. Kafka is the standard protocol, but protocol support alone is not enough. Enterprises need full feature compatibility, 24/7 support, and expert guidance for security, resilience, and cloud strategy.
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Social Commerce in Retail with Data Streaming using Apache Kafka Flink and Agentic AI
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  • 9 minute read

Data Streaming in Retail: Social Commerce from Influencers to Inventory

Social commerce is reshaping retail by merging entertainment, influencer marketing, and instant purchasing into one real-time experience. Platforms like TikTok and Instagram have become active digital storefronts where discovery and transactions happen at once. This article explains how data streaming with Apache Kafka and Flink enables retailers to power social commerce through continuous data flow, real-time inventory updates, and personalized engagement. It shows how streaming unifies marketing, operations, and AI-driven decision-making while helping retailers compete with new AI platforms such as OpenAI that are redefining digital shopping.
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Stablecoins and Data Streaming with Kafka and Flink for Digital Money and Currency USDC USDT Blockchain
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  • 10 minute read

How Stablecoins Use Blockchain and Data Streaming to Power Digital Money

Stablecoins are reshaping digital money by linking traditional finance with blockchain technology. Built for stability and speed, they enable real time payments, settlements, and programmable financial services. To operate reliably at scale, stablecoin systems require continuous data movement and analysis across ledgers, compliance tools, and banking platforms. A Data Streaming Platform using technologies like Apache Kafka and Apache Flink can provide this foundation by ensuring transactions, reserves, and risk signals are processed instantly and consistently. Together, blockchain, data streaming, and AI pave the way for a new financial infrastructure that runs on live, contextual data.
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Scaling Apache Kafka Consumers for High Throughput with Proxy or Client Library for API and Database Integration
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Scaling Kafka Consumers: Proxy vs. Client Library for High-Throughput Architectures

Apache Kafka’s pull-based model and decoupled architecture offer unmatched flexibility for event-driven systems. But as data volumes and consumer applications grow, new challenges emerge; from head-of-line blocking and rising operational overhead to complex failure handling. This post explores real-world lessons from companies like Wix and Uber, highlighting common consumer scalability issues and two main solutions: push-based consumer proxies and enhanced client libraries like Confluent’s Parallel Consumer. It concludes with a vision for a serverless Kafka consumption model that reduces total cost of ownership while preserving Kafka’s core strengths.
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Real Time Point of Sale POS in Retail and eCommerce with Data Streaming using Kafka and Flink at SumUp Square Shopify
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Square, SumUp, Shopify: Real-Time Point-of-Sale (POS) in the Age of Data Streaming

Point-of-Sale systems are evolving into real-time, connected platforms that go far beyond payments. Mobile solutions from Square, SumUp, and Shopify give even the smallest merchants access to integrated sales channels, inventory management, and customer insights. Powered by Apache Kafka and Apache Flink, data streaming is transforming retail with instant decisions, automated actions, and the foundation for Agentic AI in the future of POS.
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