The Past Present and Future of Stream Processing
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The Past, Present and Future of Stream Processing

Stream processing has existed for decades. The adoption grows with open source frameworks like Apache Kafka and Flink in combination with fully managed cloud services. This blog post explores the past, present and future of stream processing, including the relation of machine learning and GenAI, streaming databases, and the integration between data streaming and data lakes with Apache Iceberg.
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Apache Kafka vs. Middleware (MQ, ETL, ESB) – Slides + Video

This post shares a slide deck and video recording of the differences between an event-driven streaming platform like Apache Kafka and middleware like Message Queues (MQ), Extract-Transform-Load (ETL) and Enterprise Service Bus (ESB).
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Apache Kafka Streams + Machine Learning (Spark, TensorFlow, H2O.ai)

Apache Kafka Streams to build Real Time Streaming Microservices. Apply Machine Learning / Deep Learning using Spark, TensorFlow, H2O.ai, etc. to add AI. Embed Kafka Streams into Java App, Docker, Kubernetes, Mesos, anything else.
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