Ben Stopford examines tools, mechanisms and tradeoffs that allow a data architecture to scale, from disk formats to fully blown architectures for real-time storage, streaming and batch processing.
This talk goes over the design motivation for Zen and describe its internals including the API, type system and HBase backend.
Raymond Blum discusses some of the challenges, solutions and discarded alternatives in creating durable storage systems at Google scale.
Jeff Johnson introduces Apollo, a hierarchical NoSQL data system meant to deal with Facebook's distributed storage needs.
Scott Vokes presents some lesser-known data structures and shows how probability distributions and content-addressable storage can become tools to shape global system behavior.
Jeremy Edberg presents the data stores used by Netflix and Reddit, some of the best practices and lessons for surviving outages.
Nathan Herring presents the available storage options at Google, the ideal characteristics of a storage service, and the actual implementation of Google Cloud Storage.
Serkan Piantino discusses news feeds at Facebook: the basics, infrastructure used, how feed data is stored, and Centrifuge – a storage solution.
Ian Plosker explains why a data model needs to follow the query patterns when using a NoSQL storage solution.
Geir Magnusson explains why Gilt Groupe is using Project Voldemort to scale out their e-commerce transactional system, what are the benefits and what is the current architecture after ditching SQL.
In this FutureRuby talk, Ilya Grigorik explores Tokyo Cabinet's features such as the key-value store, ordered traversal, attribute search, schemaless data structures,indexing, and scripting with Lua.