Introduction to Kafka Streams with a Real-Life Example

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Hello all, we're looking forward to kicking off 2017 with an exciting Meetup on Kafka Streams given by Alexis Seigneurin. Alexis is a Managing Consultant / Big Data Engineer at Ippon Technologies USA. Alexis specializes in Big Data technologies and Data Science applications, with a strong experience on the Apache Spark framework, Machine Learning algorithms, and NoSQL databases.

Food and drink will be provided by B23, starting at 5:30. We will kick off the presentation at 6:15 sharp.


Kafka Streams is a powerful, easy-to-use library for building highly scalable, fault-tolerant, distributed stream processing applications on top of Apache Kafka. It allows developers to easily consume and process data coming from Kafka and potentially push results to another Kafka topic. In this session, I will show how, on one of our projects, Kafka Streams provided a great replacement to Spark Streaming. The code is simpler, the latency is improved and it is now a lot easier to scale the application up or down. If time permits, I will also show how we converted a batch Spark application to a Kafka Streams application and divided the processing time by two!