Viktor Gamov is a Solution Architect at Confluent, the company behind the popular Apache Kafka streaming platform.
Crossing The Streams: Rethinking Stream Processing with KStreams and KSQL
All things change constantly!
And dealing with constantly changing data at low latency is pretty hard.
It doesn't need to be that way.
Apache Kafka, the _de facto_ standard open-source distributed stream processing system.
Many of us know Kafka's architectural and pub/sub API particulars.
But that doesn't mean we're equipped to build the kind of real-time streaming data systems that the next generation of business requirements are doing to demand.
We need to get on board with streams!
Apache Kafka: A Streaming Data Platform
When it comes time to choose a distributed messaging system, everyone knows the answer: Apache Kafka. But how about when you’re on the hook to choose a world-class, horizontally scalable stream data processing system? When you need not just publish and subscribe messaging, but also long-term storage, a flexible integration framework, and a means of deploying real-time stream processing applications at scale without having to integrate a number of different pieces of infrastructure yourself? The answer is still Apache Kafka.