Apache Kafka & Apache Flink - Better Together

Over the last years, businesses have been under a lot of pressure to provide a superior customer experience: smarter, more personalised, more engaging. For this, companies need to leverage an ever-growing amount of real-time data coming from various sources.

In this context, data streaming has become a key driver of digital transformation across various industries from banking and manufacturing to online gaming and e-commerce. Apache Kafka has been at the forefront of this development and emerged as the de facto standard for reading, writing, and sharing streams across an organization.

Once these streams are reliable, governed and secured in a platform like Confluent Cloud the next step is to process them, to build applications on them and to derive insights. This is where Apache Flink comes in. Apache Flinks is a powerful stream processing framework that enables developers to address the full range of stream processing use cases: from offline analytics to real-time data pipelines to event-driven applications.

In this talk, I will briefly introduce Apache Kafka and Apache Flink and we’ll explore their role in making streaming the default for modern data architectures. Then, we’ll showcase - by example - how these two technologies become more than the sum of their parts when they are powering a cloud-native streaming platform like Confluent Cloud.