Peter Bell presents several patterns for modeling and retrieving data from graph databases using Neo4j in his examples.
Axel Morgner compares different open source CMS’s and outlines the benefits of implementing one using a graph database.
Rebecca Parsons proposes taking a different look at data, using different approaches and tools, then looks at some of the ways social data is used these days.
Eric Brewer takes a look at NoSQL’s history and considers what should be done so the current NoSQL solutions to evolve in order to address the full range of the application needs.
Jesse Newland discusses how GitHub pages were re-written with Erlang, Riak and Webmachine in order to improve their performance.
Dhruba Borthakur discusses the different types of data used by Facebook and how they are stored, including graph data, semi-OLTP data, immutable data for pictures, and Hadoop/Hive for analytics.
David Czarnecki discusses several Redis data structures and their associated libraries used in real cases for building leaderboards, relationships and activity feeds.
Sean Cribbs discusses Convergent Replicated Data Types, data structures that tolerate eventual consistency.
Justin Sheehy discusses designing reliable distributed systems that can scale in order to deal with concurrency problems and the tradeoffs required by such systems.
Andy Gross reports on how Basho used Riak and Erlang to build their cloud storage service.
Michael Stonebraker compares how RDBMS, NoSQL and NewSQL support today’s big data transaction processing needs. He also introduces VoltDB, an in-memory NewSQL database.
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.
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