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Found 2 results

  1. DZone
    Over the past few years, Apache Kafka has emerged as the leading standard for streaming data. Fast-forward to the present day: Kafka has achieved ubiquity, being adopted by at least 80% of the Fortune 100. This widespread adoption is attributed to Kafka's architecture, which goes far beyond basic messaging. Kafka's architecture versatility makes it exceptionally suitable for streaming data at a vast "internet" scale, ensuring fault tolerance and data consistency crucial for supporting mission-critical applications. Flink is a high-throughput, unified batch and stream processing engine, renowned for its capability to handle continuous data streams at scale. It seamlessly integrates with Kafka and offers robust support for exactly-once semantics, ensuring each event is processed precisely once, even amidst system failures. Flink emerges as a natural choice as a stream processor for Kafka. While Apache Flink enjoys significant success and popularity as a tool for real-time data processing, accessing sufficient resources and current examples for learning Flink can be challenging. View the full article
  2. Amazon Web Services
    Today, we are excited to announce that Amazon EMR on EKS now supports managed Apache Flink, available in public preview. With this launch, customers who already use EMR can run their Apache Flink application along with other types of applications on the same Amazon EKS cluster, helping improve resource utilization and simplify infrastructure management. For customers who already run big data frameworks on Amazon EKS, they can now let Amazon EMR automate provisioning and management. View the full article

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