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99 Ways to Enrich Streaming Data with Apache Flink
Hosted by: Konstantin Knauf | Solutions Architect at Ververica

Duration: 1h

The need to enrich a fast, high volume data stream with slow-changing reference data is probably one of the most wide-spread requirements in stream processing applications. Apache Flink's built-in join functionalities and its flexible lower-level APIs support stream enrichment in various ways depending on the specific requirements of the use case at hand. In this webinar, I like to provide an overview of the basic methods to enrich a data stream with Apache Flink and highlight use cases, limitations, advantages and disadvantages of each.
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