Jim Webber explores graph data analytic techniques using social graph properties inspired by anthropology and sociology, extracting online business intelligence from graph matching.
Kenny Gorman provides advice on designing systems using MongoDB in order to avoid some of the pitfalls lurking along the way.
Adrian Cockcroft presents Netflix globally distributed architecture, the benchmarks used, scalability issues, and the open source components their implementation is based upon.
Mark Pollack provides a guided tour plus demos of the Spring Data feature set.
Kenneth M. Anderson shares some of the data modeling issues encountered while transitioning from a relational database to NoSQL.
Matthew Dennis covers the most common mistakes made with Cassandra that he has noticed being made both in deployment and code.
Mark Little provides advice on when it is not recommended to use transactions and how to use transactions with Web Services, NoSQL, REST and mobile infrastructures.
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.
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