[ONLINE] Creating a streaming data pipeline via KsqlDB & exactly-once processing

Join our online event!
We are excited to host a special guest in this meetup - Robin Moffatt, Developer Advocate @ Confluent.

Both sessions will be delivered in English.

Agenda:
17:00 - 17:30: Exactly-once delivery is a harsh mistress: Natan Silnitsky @Wix
17:30 - 18:30: ksqlDB in Action - Let's Build a Streaming Data Pipeline: Robin Moffatt @Confluent.

First session abstract:
Is Exactly Once Delivery a pipe dream? Recent versions of Kafka have claimed they have made it a reality.

In this talk I will go over the different message delivery guarantees and the protocols that implement them. I will focus on Kafka's transaction-based messaging protocol, It’s trade-offs and shortcomings, and how it can help with many use cases that require atomic operations in today's modern distributed microservices systems.

Second session abstract:
Have you ever thought that you needed to be a programmer to do stream processing and build streaming data pipelines? Think again!
Apache Kafka is a distributed, scalable, and fault-tolerant streaming platform, providing low-latency pub-sub messaging coupled with native storage and stream processing capabilities. Integrating Kafka with RDBMS, NoSQL, and object stores is simple with Kafka Connect, which is part of Apache Kafka. ksqlDB is the event streaming database for Apache Kafka, and makes it possible to build stream processing applications at scale, written using a familiar SQL interface.

In this talk, we’ll explain the architectural reasoning for Apache Kafka and the benefits of real-time integration, and we’ll build a streaming data pipeline using nothing but our bare hands, Kafka Connect, and ksqlDB.
Gasp as we filter events in real-time! Be amazed at how we can enrich streams of data with data from RDBMS! Be astonished at the power of streaming aggregates for anomaly detection!

Robin Moffatt is a Developer Advocate at Confluent and an ambassador of streaming architecture. You can follow Robin's tweets at https://twitter.com/rmoff and read his posts at https://rmoff.net/.