There is something very interesting about stream processing. It builds upon messaging, rather than using a file system, as a more typical database does. But stream processing engines themselves are really a type of database. A database designed specifically to blend streams and tables so you can query continuous results. As such they span an architectural no-mans-land that sits between Database and Distributed Systems fields.
This talk will look at Stateful Stream Processing. Can a streaming engine provide the guarantees of a database? When is a streaming engine best? How do they work, under the covers?
Ben is an engineer and architect working on the Apache Kafka Core Team at Confluent Inc (the company behind Apache Kafka). He's worked with distributed data infrastructure for the last ten years, switching between engineering products and helping companies use them. His early career spanned a variety of projects at Thoughtworks and UK-based enterprise companies.
He writes at benstopford.com.