Kafka Streams vs. KSQL for Stream Processing on top of Apache Kafka®

Details
Join us for an Apache Kafka® meetup on May 21st from 6:00pm, hosted at Swisscom in Zurich. The address, agenda and speaker information can be found below. See you there!

6:00pm: Doors open
6:00pm - 6:30pm: Pizza, Drinks and Networking
6:30pm - 7:15pm: Kai Waehner, Confluent
7:15pm - 7:45pm: Philipp Schlegel and Herbert Wespi, Swisscom
7:45pm - 8:00pm - Additional Q&A & Networking

Talk 1:

Speaker: Kai Waehner/ Confluent

Title of Talk: Spoilt for Choice – Kafka Streams vs. KSQL for Stream Processing on top of Apache Kafka®

Bio:
Kai Waehner works as Technology Evangelist at Confluent. Kai’s main area of expertise lies within the fields of Big Data Analytics, Machine Learning / Deep Learning, Cloud / Hybrid Architectures, Messaging, Integration, Microservices, Stream Processing, Internet of Things and Blockchain. He is regular speaker at international conferences such as JavaOne, O’Reilly Software Architecture or ApacheCon, writes articles for professional journals, and shares his experiences with new technologies on his blog (www.kai-waehner.de/blog). He also writes at https://cnfl.io/blog-kai-waehner. Contact and references: kontakt@kai-waehner.de / @KaiWaehner / www.kai-waehner.de

Abstract:
Apache Kafka is a de facto standard streaming data processing platform. It is widely deployed as event streaming platform. Part of Kafka is its stream processing API “Kafka Streams”. In addition, the Kafka ecosystem now offers KSQL, a declarative, SQL-like stream processing language that lets you define powerful stream-processing applications easily. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax.

This session discusses and demos the pros and cons of Kafka Streams and KSQL to understand when to use which stream processing alternative for continuous stream processing natively on Apache Kafka infrastructures. The end of the session compares the trade-offs of Kafka Streams and KSQL to separate stream processing frameworks such as Apache Flink or Spark Streaming.

Talk 2:

Speaker: Philipp Schlegel, Dr. sc.

Title of Talk: Using Kafka in a Closed Environment with Centralized Orchestration

Bio:
Team Lead at Consulting and Software Engineering Banking, Swisscom

Abstract:
Kafka is often used in open, decentralized systems that do not require any orchestration at all. However, Kafka can also be used in closed systems that require event orchestration to execute a processing flow. I'll show an approach towards a closed, centralized orchestration.

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Talk 3:

Speaker: Herbert Wespi, Software Developer

Title of Talk: Relations between Domain Entities in Kafka Key-Value Stores

Bio:
Consultant and Enterprise Software Engineer at Swisscom

Abstract:
We use Kafka not only for processing events, but as well to persist data. Maintaining relationships between entities are not yet supported out of the box. I will talk about different approaches we considered and what our final solution for this problem looks like.

Don't forget to join our Community Slack Team! https://launchpass.com/confluentcommunity

If you would like to speak or host our next event please let us know! community@confluent.io

NOTE: We're unable to cater for attendees under the age of 18. Please do not sign up for this event if you're under 18.