Google Dataflow: The new open model for batch and stream processing
In 2004 MapReduce was introduced, a model that kick-started big data. 10 years later, Google published Dataflow - a new paradigm, integrating batch and stream processing in one common abstraction. This time it was more than a paper, but also an open source Java SDK and a cloud managed service to run it. In 2016 Dataflow was proposed for incubation at the Apache Software Foundation - Beam was born, unifying batch and streaming, and also the big data world. We’ll demonstrate Dataflow’s capabilities through a real-time demo with practical insights on how to manage and visualize streams of data.
Robert Kubis is a developer advocate for Google Cloud Platform based in London, UK, specializing in container, storage, and scalable technologies. Before joining Google, Robert collected over 10 years of experience in software development and architecture. He has driven multiple full-stack application developments at SAP with a passion for distributed systems, containers, and databases. In his spare time he enjoys following tech trends and good restaurants, traveling, and improving his photography skills.