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44 posts
JavaScript Node JS Apache Kafka for Full Stack Data Streaming in Event Driven Architecture
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  • 7.1K views
  • 10 minute read

JavaScript, Node.js and Apache Kafka for Full-Stack Data Streaming

JavaScript is a pivotal technology for web applications. With the emergence of Node.js, JavaScript became relevant for both client-side and server-side development, enabling a full-stack development approach with a single programming language. Both Node.js and Apache Kafka are built around event-driven architectures, making them naturally compatible for real-time data streaming. This blog post explores open-source JavaScript Clients for Apache Kafka and discusses the trade-offs and limitations of JavaScript Kafka producers and consumers compared to stream processing technologies such as Kafka Streams or Apache Flink.
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Tiered Storage for Apache Kafka - Use Cases Architecture Benefits.png
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  • 8.6K views
  • 11 minute read

Why Tiered Storage for Apache Kafka is a BIG THING…

Apache Kafka added Tiered Storage to separate compute and storage. The capability enables more scalable, reliable and cost-efficient enterprise architectures. This blog post explores the architecture, use cases, benefits, and a case study for storing Petabytes of data in the Kafka commit log. The end discusses why Tiered Storage does NOT replace other databases and how Apache Iceberg might change future Kafka architectures even more.
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The State of Data Streaming for the Public Sector in 2023
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  • 2.4K views
  • 5 minute read

The State of Data Streaming for the Public Sector

This blog post explores the state of data streaming for the public sector and government. Data streaming provides consistency across all layers and allows integrating and correlating data in real-time at any scale. I look at public sector trends to explore how Apache Kafka helps as a business enabler, including case studies from the US Department of Defense (DoD), NASA, Deutsche Bahn (German Railway), and others. A complete slide deck and on-demand video recording are included.
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Apache Kafka and Apache Flink for Open Source and Cloud-native Data Streaming
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  • 15.8K views
  • 12 minute read

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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Data Streaming Landscape 2023 with Apache Kafka Flink and much more
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  • 7.8K views
  • 13 minute read

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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Cloud Native SCADA Industrial IoT with Apache Kafka Data Streaming
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  • 6 minute read

A cloud-native SCADA System for Industrial IoT built with Apache Kafka

Industrial IoT and Industry 4.0 enable digitalization and innovation. SCADA control systems are a vital component of IT/OT modernization. The SCADA evolution started with monolithic applications and moved to networked and web-based platforms. This blog post explores building the 5th generation: A cloud-native SCADA infrastructure with Apache Kafka. A real-world case study explores the journey of a German system operator for electricity to show how such a journey to open and scalable real-time workloads and edge-to-cloud integration progressed.
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Kafka versus HTTP REST API
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  • 10.3K views
  • 11 minute read

Request-Response with REST/HTTP vs. Data Streaming with Apache Kafka – Friends, Enemies, Frenemies?

Request-response communication with REST / HTTP is simple, well understood, and supported by most technologies, products, and SaaS cloud services. Contrarily, data streaming with Apache Kafka is a fundamental change to process data continuously. HTTP and Kafka complement each other in various ways. This post explores the architectures and use cases to leverage request-response together with data streaming in the control plane for management or in the data plane for producing and consuming events.
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Cloud Native Core Banking Platform powered by Apache Kafka Data Streaming
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  • 10 minute read

Cloud-native Core Banking Modernization with Apache Kafka

Most financial service institutions operate their core banking platform on legacy mainframe technologies. The monolithic, proprietary, inflexible architecture creates many challenges for innovation and cost-efficiency. This blog post explores three open, elastic, and scalable banking solutions powered by Apache Kafka to solve these problems.
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Apache Kafka Transactions API vs Big Data Lake and Batch Analytics
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  • 6.0K views
  • 9 minute read

Analytics vs. Transactions in Data Streaming with Apache Kafka

Workloads for analytics and transactions have very unlike characteristics and requirements. Many people think that Apache Kafka is not built for transactions and should only be used for big data analytics. This blog post explores when and how to use Kafka in resilient, mission-critical architectures and when to use the built-in Transaction API.
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Apache Camel vs Apache Kafka Comparison
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  • 17.3K views
  • 13 minute read

When to use Apache Camel vs. Apache Kafka?

Should I use Apache Camel or Apache Kafka for my next integration project? The question is very valid and comes up regularly. This blog post explores both open-source frameworks and explains the difference between application integration and event streaming. The comparison discusses when to use Kafka or Camel, when to combine them, when not to use them at all. A decision tree shows how you can quickly qualify out one for the other.
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