When NOT to Use Apache Kafka?
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When NOT to Use Apache Kafka? (Lightboard Video)

Apache Kafka is the de facto standard for data streaming to process data in motion. With its significant adoption growth across all industries, I get a very valid question every week: When NOT to use Apache Kafka? What limitations does the event streaming platform have? When does Kafka simply not provide the needed capabilities? How to qualify Kafka out as it is not the right tool for the job? This blog post contains a lightboard video that gives you a twenty-minute explanation of the DOs and DONTs.
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Innovation in Financial Services and Open Banking with Apache Kafka
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Apache Kafka in the Financial Services Industry

The rise of event streaming in financial services is growing like crazy. Continuous real-time data integration and processing are mandatory for many use cases. Apache Kafka is deployed across the financial services business departments for mission-critical transactional workloads and big data analytics. High scalability, high reliability, and an elastic open infrastructure are the key reasons for the success of Kafka. This blog post explores different use cases, architectures, and real-world examples in the FinServ sector.
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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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