日本語

Stream data processing 101

There’s an increasing demand for stream data processing, which processes ever-occurring data in real-time, visualizes the results, or handles the resulting event. In this session, we will explore some of the aspects of how it tackles the issues unsolved by batch processing and what technology it newly enables. Many stream data processing platforms have emerged in recent years, for instance Spark Streaming, Flink, Apex, Gearpump, and Beam; so many, in fact, that it’s unclear from the users’ perspective where we are headed. By illustrating the history of stream data processing on the JVM, along with comparison of products that came out in the last few years, I hope to clarify the key points of the platforms that developers should understand when building a stream data processing system.

Session length
40 minutes
Language of the presentation
Japanese
Target audience
Intermediate: Requires a basic knowledge of the area
Speaker
Sotaro Kimura

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