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Confluent, Kafka, Druid, and Flink: The Future of Streaming Data with Kai Waehner

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Content provided by Imply Data. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Imply Data or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Apache Kafka® is a streaming platform that can handle large-scale, real-time data streams reliably. It’s used for real-time data pipelines, event sourcing, log aggregation, stream processing, and building analytics applications. Apache® Druid is a database designed to provide fast, interactive, and scalable analytics on time-series and event-based data, empowering organizations to derive insights, monitor real-time metrics, and build analytics applications. Naturally, these two things just go together and are often both key parts of a company’s data architecture. Confluent is one of those companies. On this episode, Kai Waehner, Field CTO at Confluent walks us through how they use Kafka and Druid together, where Apache Flink fits into the mix and shares insights and trends from the world of data streaming.

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31 episodes

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Manage episode 377233877 series 3512228
Content provided by Imply Data. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Imply Data or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Apache Kafka® is a streaming platform that can handle large-scale, real-time data streams reliably. It’s used for real-time data pipelines, event sourcing, log aggregation, stream processing, and building analytics applications. Apache® Druid is a database designed to provide fast, interactive, and scalable analytics on time-series and event-based data, empowering organizations to derive insights, monitor real-time metrics, and build analytics applications. Naturally, these two things just go together and are often both key parts of a company’s data architecture. Confluent is one of those companies. On this episode, Kai Waehner, Field CTO at Confluent walks us through how they use Kafka and Druid together, where Apache Flink fits into the mix and shares insights and trends from the world of data streaming.

  continue reading

31 episodes

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