InfoQ Homepage NoSQL Content on InfoQ
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Introduction to Spring Data Neo4j
Michael Hunger discusses graph databases and the need for them in the larger context of NoSQL data stores, introducing Spring Data, Neo4j, and Spring Data Neo4j.
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Case Study: Riak on Drugs (and the Other Way Around)
Kresten Krab Thorup discusses a MySQL project that was moved to Riak for high availability, scalability and to run off multiple data centers, sharing the experiences, pitfalls and lessons learned.
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SQLFire: Scalable SQL instead of NoSQL
Jags Ramnaraya presents SQLFire and how SQL can be used for modern data stores backing online highly scalable applications by using a different consistency model and sharing nothing persistence.
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Using A Graph Database To Power The “Web of Things”
Rick Bullotta and Emil Eifrem discuss how to use graph databases to model the real world, people, systems and things, talking advantage of the relationships between various data elements.
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HBase @ Facebook
Kannan Muthukkaruppan overviews HBase, explaining what Facebook Messages is and why they chose HBase to implement it, their contribution to HBase, and what they plan to use it for in the future.
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Nokia: Lessons Learnt Migrating a Very Large and Highly Relational Database into a "Classic" NoSQL
Enda Farrell discusses how they ported Nokia’s places registry to NoSQL, the reasons, the complexity involved and the lessons learned along the way in terms of people, tools and data.
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Membase NoSQL: Clustered by Erlang
Sean Lynch and Matt Ingenthron introduce Membase, detailing how they added clustering features in Erlang, what they built and what lessons they leaned along the way.
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Why I Chose MongoDB for guardian.co.uk
Mat Wall makes a journey through Guardian’s online history, outlining technologies used – Perl/CGI, CMS, J2EE, Oracle-, and explaining why they chose a NoSQL solution – MongoDB - and its advantages.
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Things Break, Riak Bends
Justin Sheehy talks about failure and the need to prepare for it, giving some real life examples along with techniques implemented in Riak to make it resilient to faults.
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Building Solid Distributed Applications with Haskell and Riak
Bryan O'Sullivan discusses the design considerations and types usage when building distributed systems with Haskell and Riak, starting from a case study of a system using vector clocks.
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Big Data in Real Time at Twitter
Nick Kallen discusses how Twitter handles large amounts of data in real time by creating 4 data types and query patterns -tweets, timelines, social graphs, search indices-, and the DBs storing them.
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NoSQL @ Netflix
Siddharth “Sid” Anand explains the technical details behind the move from Oracle used inside their data center to SimpleDB and S3 in the cloud, and from there to Cassandra.
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