The State of Data Streaming for Manufacturing in 2023
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The State of Data Streaming for Manufacturing

This blog post explores the state of data streaming for manufacturing. The evolution of industrial IoT, manufacturing 4.0, and digitalized B2B and customer relations require modern, open, and scalable information sharing. The foci are trending enterprise architectures in the manufacturing industry and data streaming customer stories from BMW, Mercedes, Michelin, or Siemens. A complete slide deck and on-demand video recording are included.
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JMS Message Broker vs Apache Kafka Data Streaming
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Message Broker and Apache Kafka: Trade-Offs, Integration, Migration

A Message broker has very different characteristics and use cases than a data streaming platform like Apache Kafka. Data integration, processing, governance, and security must be reliable and scalable across the business process. This blog post explores the capabilities of message brokers, the relation to the JMS standard, trade-offs compared to data streaming with Apache Kafka, and typical integration and migration scenarios.
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Global Supply Chain with IoT and Data Streaming
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Transforming the Global Supply Chain with Data Streaming and IoT

The research company IoT Analytics found eight key technologies transforming the future of the global supply chain. This article explores how data streaming helps to innovate in this area. Real-world case studies from global players such as BMW, Bosch, and Walmart show the value of real-time data streaming to improve the supply chain by building use cases such as automated intralogistics, track and trace of vehicles, and proactive and context-specific decision-making with MES and ERP integration. 
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Apache Kafka and Apache Flink for Open Source and Cloud-native Data Streaming
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Apache Kafka (including Kafka Streams) + Apache Flink = Match Made in Heaven

Apache Kafka and Apache Flink are increasingly joining forces to build innovative real-time stream processing applications. This blog post explores the benefits of combining both open-source frameworks, shows unique differentiators of Flink versus Kafka, and discusses when to use a Kafka-native streaming engine like Kafka Streams instead of Flink.
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Apache Kafka for Data Consistency (and Real-Time Data Streaming)
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Apache Kafka for Data Consistency (and Real-Time Data Streaming)

Real-time data beats slow data in almost all use cases. But as essential is data consistency across all systems, including non-real-time legacy systems and modern request-response APIs. Apache Kafka’s most underestimated feature is the storage component based on the append-only commit log. It enables loose coupling for domain-driven design with microservices and independent data products in a data mesh. This blog post explores how Kafka enables data consistency with a real-world case study from financial services.
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Data Streaming Landscape 2023 with Apache Kafka Flink and much more
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The Data Streaming Landscape 2023

Data streaming is a new software category to process data in motion. Apache Kafka is the de facto standard used by over 100,000 organizations. Plenty of vendors offer Kafka platforms and cloud services. Many complementary stream processing engines like Apache Flink and SaaS offerings have emerged. And competitive technologies like Pulsar and Redpanda try to get market share. This blog post explores the data streaming landscape of 2023 to summarize existing solutions and market trends.
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Top Use Cases and Architectures for Data Streaming with Apache Kafka in 2023
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Top 5 Data Streaming Trends for 2023

Data Streaming is one of the most relevant buzzwords in tech to build scalable real-time applications in the cloud and innovative business models. Do you wonder about my predicted TOP 5 data streaming trends in 2023 to set data in motion? Check out the following presentation and learn what role Apache Kafka plays. Learn about decentralized Data Mesh, cloud-native lakehouse, data sharing, improved user experience, and advanced data governance.
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Apache Kafka vs Redpanda Comparison
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When to choose Redpanda instead of Apache Kafka?

Data streaming emerged as a new software category. It complements traditional middleware, data warehouse, and data lakes. Apache Kafka became the de facto standard. New players enter the market because of Kafka’s success. One of those is Redpanda, a lightweight Kafka-compatible C++ implementation. This blog post explores the differences between Apache Kafka and Redpanda, when to choose which framework, and how the Kafka ecosystem, licensing, and community adoption impact a proper evaluation.
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Decentralized Data Mesh with Data Streaming in Financial Services and Banking
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Decentralized Data Mesh with Data Streaming in Financial Services

Digital transformation requires agility and fast time to market as critical factors for success in any enterprise. The decentralization with a data mesh separates applications and business units into independent domains. Data sharing in real-time with data streaming helps to provide information in the proper context to the correct application at the right time. This blog post explores a case study from the financial services sector where a data mesh was built across countries for loosely coupled data sharing but standardized enterprise-wide data governance.
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