The authors take a deep dive into the history of NoSQL at Amazon.com, from the world of relational databases to the Dynamo days to the world of managed services like DynamoDB.
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications.
Chad DePue presents the process of building Edis, a Redis clone written in Erlang, allowing pluggable backends and implementing the Paxos algorithm.
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
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.