Siva Raghupathy discusses DynamoDB Design Patterns & Best Practices for realizing DynamoDB benefits at the right cost.
Shanley Kane discusses Dynamo - consistent hashing, vector clocks, hinted handoff, gossip protocol - advances in each area, and how querying and application development has changed as a result of them.
David Czarnecki discusses several Redis data structures and their associated libraries used in real cases for building leaderboards, relationships and activity feeds.
Peter Bell introduces 4 NoSQL categories –Key-Value, Document, Column, Graph - and explains how one can use Spring Data to work with such data stores.
Chris Meadows introduces Redis, explaining what it is good for, what does it take to be run, and what’s under the hood through a social networking code example.
Susan Potter discusses Dynamo, Riak, distribution, consistency and fault tolerance, along with techniques and an example for building an application with riak_core.
Chris Richardson shows how he ported a relational database to three NoSQL data stores: Redis, Cassandra and MongoDB.
Shaneal Manek tells the story of how things can go wrong with a distributed system which turned into a success after incorporating appropriate tools for monitoring, analytics, logging, security.
Scott Lystig Fritchie presents the architecture and lessons learned implementing a webmail system in Erlang, using UBF and Hibari, a distributed key-value store, to accommodate a large user base.
Ryan King presents how Twitter uses NoSQL technologies - Gizzard, Cassandra, Hadoop, Redis - to deal with increasing data amounts forcing them to scale out beyond what the traditional SQL has to offer.
Adam Wiggins believes that now is the time of horizontal scalability achieved by using resources that are transient, shardable and share nothing with other resources. He gives as example several applications and a language: memcached, CouchDB, Hadoop, Redis, Varnish, RabbitMQ, Erlang, detailing how each one applies those principles.
In this presentation from QCon San Francisco 2009, Billy Newport discusses the ways that developers interact with key/value (KV) stores such as memcached and WebSphere eXtreme Scale, entity vs column-oriented approaches, synchronous and asynchronous operations, large data sets, using a DBMS as a column store, collocating closures and data, and features that could be added to increase scalability.