InfoQ Homepage Big Data Content on InfoQ
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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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Building Scalable Systems: an Asynchronous Approach
Theo Schlossnagle expresses his opinion on Big Data, NoSQL, cloud, system architecture and design, then he discusses the benefit of using asynchronous queues for building scalable systems.
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Using Spring with NoSQL Databases
Mark Pollack and Chris Richardson discuss NoSQL, exemplifying with Redis, Cassandra and MongoDB, and Spring Data, a project meant to provide a unified programming model for accessing NoSQL DBs.
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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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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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Large Scale Map-Reduce Data Processing at Quantcast
Ron Bodkin presents the architecture used by Quantcast to process 100s of TB of data daily using Hadoop on dedicated systems, the applications, the type of data processed, and the infrastructure used.
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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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Adopting Apache Cassandra
Eben Hewitt introduces the Apache Cassandra project to those interested in getting a quick clear picture of what Cassandra is, what are its main features, what is the the data model used and the API.
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