Life doesn't happen in batch mode, which is why for several years now, we see a very strong tendency towards stream processing throughout various industries. Companies need, or least partially have to rethink their existing data architectures in order to enable near real-time business cases. Besides traditional database systems and batch-driven tooling, many companies put Apache Kafka® - the de facto standard for robust and scalable event streaming - to good use. This talk explores the following four different ways to run Kafka on Azure: * Kafka on HDInsight (open-source core Kafka) * EventHubs (Microsoft's very own "Kafka look-alike") * Confluent Cloud (a vendor-backed Kafka distribution) * Kafka in Azure Kubernetes Service You will walk away with a better understanding about the most important benefits, drawbacks and implications for each of the discussed alternatives.
Hans-Peter is a technical trainer for Java backend development and is responsible for the internal education department at NETCONOMY Software & Consulting GmbH in Graz, Austria. As an independent engineer and consultant he is supporting customers during the conception and implementation of either cloud-based or on-premises data architectures using modern technology stacks and NoSQL data stores. He is also an associate lecturer for Software Engineering at CAMPUS 02 University of Applied Sciences and is speaking at tech-related and developer conferences. For his code contributions, conference talks and blog post writing at the intersection of the Apache Kafka and MongoDB ecosystems, Hans-Peter received the Confluent Community Catalyst award twice (2019-2020 & 2020-2021) and became one of the founding members of the MongoDB Champions Program in late 2020.
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