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.
Fred Hebert discusses using Erlang for a real-time bidding system, providing some details of its design and architecture, along with lessons learned while implementing it.
Serkan Piantino discusses news feeds at Facebook: the basics, infrastructure used, how feed data is stored, and Centrifuge – a storage solution.
Raffi Krikorian details Twitter’s timeline architecture, its “write path” and “read path”, making it possible to deliver 300k tweets/sec.
Richard Tibbetts presents a three-tier architecture for real-time data staging analysis, storing the results and delivering them to clients as a service accessible through a variety of interfaces.
Nathan Marz discusses Storm concepts –streams, spouts, bolts, topologies-, explaining how to use Storms’ Clojure DSL for real-time stream processing, distributed RPS and continuous computations.
Trotter Cashion introduces and demoes Chloe, a web server that handles real time data streaming between browsers and web applications written in any language and using any framework.
David Pollak discusses predicates, dependencies, functional languages and programming for the real-time cloud.
Nick Kallen discusses how Twitter handles large amounts of data in real time by creating 4 data types and query patterns -tweets, timelines, social graphs, search indices-, and the DBs storing them.