Alvaro Videla shows how to build a system that can ingest data produced at separate locations and replicate it across regions using RabbitMQ.
Jeff Johnson introduces Apollo, a hierarchical NoSQL data system meant to deal with Facebook's distributed storage needs.
Alvaro Videla presents the more advanced features of RabbitMQ: federated brokers, HA queues and support for many protocols and languages.
Cliff Click introduces a coding style & API for in-memory analytics that handles datasets from 1K to 1TB without changing a line of code and clusters with TB of RAM and hundreds of CPUs.
Sebastian Kanthak overviews Spanner, covering details of how Spanner relies on GPS and atomic clocks to provide two of its most innovative features: Lock-free strong (current) reads and global snapshots that are consistent with external events.
Ian Plosker shares a number of techniques for establishing the data query patterns from the outset of application development, designing a data model to fit those patterns.
Adrian Cockcroft presents Netflix globally distributed architecture, the benchmarks used, scalability issues, and the open source components their implementation is based upon.
Hairong Kuang explains how Facebook uses HDFS to store and analyze over 100PB of user log data.
Neha Narula provides advice on choosing a data store for a web applications and executing distributed queries.
Mark Johnson and David Turanski introduce Spring Data for GemFire demoing using Spring Data for persistency across multiple distributed database grids.
Yaniv Rodenski introduces Hadoop, then running Hadoop on Azure and the available tools and frameworks.