Dan Frank discusses stream data processing and introduces NSQ – Bitly’s open source queuing system – and other new technologies used for communication between streaming programs.
Oleg Zhurakousky discusses architectural tradeoffs and alternative implementations of real-time high speed data ingest into Hadoop.
Mike Nolet shares lessons learned scaling AppNexus and architectural details of their system processing 30TB/day: Hadoop, load balancer-free DNS architecture built in GSLB and Keepalived, and real-time data streaming built in C.
Bijan Vaez discusses building large-scale cross-platform mobile apps with HTML5 including offline support, real-time interactivity, and device APIs (camera, GPS).
Gustavo Garcia explores actual use cases for real time communication in verticals ranging from telepresence to healthcare, where WebRTC fits and where it falls short, and what developers can do.
Charles Cai, Ashwani Roy discuss a robust, cost effective, hypothetical solution to address extreme challenges in financial institutions, from decision making support to pricing and risk management.
Nikita Ivanov shows adding real-time capabilities to Hadoop through a demo application streaming word counting on a 2-nodes cluster.
Sam Aaron promotes the benefits of Live Programming using interactive editors, REPL sessions, real-time visuals and sound, live documentation and on-the-fly-compilation.
Owen Barnes introduces SocketStream, a Node.js framework for building single-page real-time web applications that access all of their data via WebSocket.
Daniel Erickson addresses the problems appearing in mixing MVC and real time frameworks in web applications and how Geddy transparently solves these issues.
Guillermo Rauch investigates how some technologies – WebSocket, SPDY, WebRTC, HTTP 2.0 – help with real-time web.
Ross Mason explains what real-time API is, the corresponding technologies and trends, demoing using streaming APIs.