Data Streaming Meets Data Lake and Lakehouse with Apache Iceberg and Delta Lake
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Data Streaming Meets Lakehouse: Apache Iceberg for Unified Real-Time and Batch Analytics

Apache Iceberg is gaining momentum as the open table format of choice for modern data architectures. In this blog post, the key takeaways from my talk at Open Source Data Summit are shared, along with the full video and downloadable slides. The session explores how Iceberg fits into real-time data streaming with Apache Kafka and Flink, why streaming into a data lake is complex, and what patterns actually work in production. It also covers technical challenges like schema evolution, compaction, and governance — and how to solve them. Watch the session, review the slides, and learn how Iceberg helps build reliable, streaming-powered data products at scale.
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Stablecoins and Data Streaming with Kafka and Flink for Digital Money and Currency USDC USDT Blockchain
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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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Cybersecurity with a Real-Time Digital Twin using Data Streaming with Apache Kafka Flink and Sigma
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Cybersecurity with a Digital Twin: Why Real-Time Data Streaming Matters

Cyberattacks on critical infrastructure and manufacturing are growing, with ransomware and manipulated sensor data creating severe risks. Digital twins combined with data streaming provide real-time visibility, continuous monitoring, and proactive defense across both IT and OT environments. Using technologies like Kafka, Flink and Sigma, organizations can detect anomalies instantly, strengthen resilience, and secure digital transformation.
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The Future of AI-Ready Integration with Data Streaming powered by Apache Kafka and Flink
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How Siemens, SAP, and Confluent Shape the Future of AI Ready Integration – Highlights from the Rojo Event in Amsterdam

Many enterprises want to become AI ready but are limited by slow, batch based integration platforms that prevent real time insight and automation. The Rojo “Future of Integration” event in Amsterdam addressed this challenge by bringing together Siemens, SAP, Rojo, and Confluent to show how event driven and intelligent data architectures solve it. The discussions revealed how data streaming with Apache Kafka and Flink complements traditional integration tools, enabling continuous data flow, scalability, and the foundation for AI and automation. This blog summarizes the key learnings from the event, including my presentation “AI Ready Integration with Data Streaming,” and insights from Siemens, SAP, and Rojo on how enterprises can build truly connected, AI ready ecosystems.
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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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Online Feature Store for AI ML with Data Streaming using Apache Kafka Flink FlinkSQL Confluent Cloud at Wix
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Online Feature Store for AI and Machine Learning with Apache Kafka and Flink

Real-time personalization requires more than just smart models. It demands fresh data, fast processing, and scalable infrastructure. This blog post explores how Wix.com rebuilt its online feature store using Apache Kafka and Flink, turning their AI architecture into a real-time powerhouse that supports personalized experiences for millions of users.
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The Future of Data Streaming with Apache Flink for Agentic AI Supporting A2A and MCP
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The Future of Data Streaming with Apache Flink for Agentic AI

Agentic AI is moving into production. Autonomous, tool-using, goal-driven systems that need real-time data and context. Apache Kafka and Flink provide the event-driven foundation to run these agents at scale. With the new Flink Agents project (FLIP-531), Flink will natively support long-running, system-triggered AI agents integrated with LLMs, tools, and emerging protocols like MCP and A2A. This marks a major step toward reliable, enterprise-grade Agentic AI.
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Data Streaming and AI in the Automotive Industry at OEMs like Porsche Tesla BMW
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Driving the Future: How Real-Time Data Streaming Is Powering Automotive Innovation

The automotive industry is rapidly shifting toward a software-defined, data-driven future. Real-time technologies like Apache Kafka and Apache Flink are now critical to powering connected vehicles, smart factories, autonomous platforms, and personalized mobility services. This blog explores how leading OEMs and suppliers use data streaming to drive digital transformation – from edge processing and AI to predictive maintenance and customer experience. As the industry moves toward intelligent, adaptive systems, event-driven architecture becomes a strategic foundation.
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Agentic AI with AWS Amazon Bedrock AgentCore and Data Streaming using Apache Kafka Flink and Confluent Cloud
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Building Agentic AI with Amazon Bedrock AgentCore and Data Streaming Using Apache Kafka and Flink

Agentic AI goes beyond chatbots. These are autonomous systems that observe, reason, and act—continuously and in real time. At AWS Summit New York 2025, Amazon launched Bedrock AgentCore to build and operate secure, scalable AI agents. But to run in production, agents also need real-time data, continuous context, and flexible integration. That’s where data streaming with Apache Kafka and Apache Flink comes in. Combined with open standards like MCP and A2A, they provide the event-driven foundation for always-on, enterprise-grade AI agents.
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