InfoQ Homepage NoSQL Content on InfoQ
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Riak Core: Dynamo Building Blocks
Andy Gross discusses the design philosophy behind Riak based on Amazon Dynamo - Gossip Protocol, Consistent Hashing, Vector clocks, Read Repair, etc. -, overviewing its main features and architecture.
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Scaling with MongoDB
Roger Bodamer provides advice on scaling out MongoDB using replica sets and auto-sharding, plus tips for database deployment and scaling use cases.
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Yes, SQL!
Uri Cohen presents the key characteristics of SQL and NoSQL databases and how to create a layer on top of distributed data stores in order to use SQL to query for data.
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Panel: Non-Relational Data Stores
Roger Bodamer, Chris Biow, Steve Harris, Rusty Klophaus, Mike Malone, and Ken Sipe (panel moderator) discuss the future development of NoSQL or non-relational data stores.
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Consistency Models in New Generation Databases
Roger Bodamer talks about consistency models in NoSQL databases, showing how different products deal with replication, multiple copies of information, consistency, failover, high availability.
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Webmail for Millions, Powered by Erlang
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.
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NoSQL at Twitter
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
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Enterprise NoSQL: Silver Bullet or Poison Pill?
Billy Newport explains the fundamental differences between SQL and NoSQL, creating awareness that NoSQL is not suited for many cases, and people should make informed decisions before buying into it.
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NoSQL at Twitter
Kevin Weil presents how Twitter does data analysis using Scribe for logging, base analysis with Pig/Hadoop, and specialized data analysis with HBase, Cassandra, and FlockDB.
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Yes, SQL!
Uri Cohen reviews SQL and distributed data stores, presenting how various API’s – memcached, SQL/JDBC, JPA - can be used to interact with such data stores, specifying what jobs they are best used for.
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HyperGraphDB - Data Management for Complex Systems
Borislav Iordanov presents the architecture of HyperGraphDB, a special type of store based on hypergraphs – graphs with edges pointing to an arbitrary number of nodes and to other edges.
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Abstractions at Scale–Our Experiences at Twitter
Marius Eriksen considers that leaky abstractions lead to scalability issues, while those providing narrow access to explicit resources - map-reduce, shared-nothing web apps, big table - scale better.
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