Qantas Airline Data Streaming Platform with Apache Kafka for Airline Operations
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From Takeoff to Touchdown: Real-Time Aviation with Data Streaming at Qantas

This blog post explores how data streaming transforms airline operations by enabling real-time visibility, faster decision-making, and improved customer experience. Using Qantas as a leading example, it highlights how a modern data streaming platform powered by Apache Kafka supports flight operations, crew coordination, baggage handling, and airport collaboration. It also explains technical integrations using Kafka Connect for AIDX message processing. The Qantas story illustrates how real-time data creates tangible business value across the aviation industry.
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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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Diskless Kafka at FinTech Robinhood for Cost-Efficient Log Analytics and Observability with WarpStream
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Diskless Kafka at FinTech Robinhood for Cost-Efficient Log Analytics and Observability

Diskless Kafka is transforming how fintech and financial services organizations handle observability and log analytics. By using the Kafka protocol with cloud-native object storage, companies like Robinhood reduce infrastructure costs and gain elastic scalability. This article explores how Robinhood leverages Kafka, Flink, and WarpStream to build a real-time platform that supports trading, monitoring, and compliance at scale.
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Data Streaming in Automotive Industry with Apache Kafka and Flink for Connected Vehicles Cars using Shift Left Architecture Telemetry Signal Processing
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Shift Left in Automotive: Real-Time Intelligence from Vehicle Telemetry with Data Streaming at Rivian

Rivian and Volkswagen, through their joint venture RV Tech, process high-frequency telemetry from connected vehicles using Apache Kafka and Apache Flink. With a shift left architecture and smart filtering, they reduced data volume by 88 percent and enabled over 250 downstream consumer applications to access curated data products. This blog explores how RV Tech transforms raw vehicle data into real-time intelligence, supporting use cases across engineering, operations, and customer experience.
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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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Stream Processing on the IBM Mainframe with Apache Flink - Genius or a Glitch in the Matrix
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Stream Processing on the Mainframe with Apache Flink: Genius or a Glitch in the Matrix?

Running Apache Flink on a mainframe may sound surprising, but it is already happening and for good reason. As modern mainframes like IBM z17 evolve to support Linux, Kubernetes, and AI workloads, they are becoming a powerful platform for real-time stream processing. This blog explores why enterprises are deploying Apache Flink on IBM LinuxONE, how it works in practice, and what business value it brings. With Kafka providing the data backbone, Flink enables intelligent processing close to where business-critical data lives. The result is a modern hybrid architecture that connects core systems with cloud-based innovation without needing to fully migrate off the mainframe.
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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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