InfoQ Homepage Database Content on InfoQ
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Big Data Problems in Monitoring at eBay
Bhaven Avalani and Yuri Finklestein discuss 4 aspects encountered at eBay when dealing with monitoring data: reduction of data entropy, robust data distribution, metric extraction, efficient storage.
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100% Big Data, 0% Hadoop, 0% Java
Pavlo Baron presents a big data case, a solution and the tools for collecting, mining and storing large amounts of data without using Hadoop or Java.
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NoSQL: Past, Present, Future
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.
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Big Data, Small Computers
Cliff Click discusses RAIN, H2O, JMM, Parallel Computation, Fork/Joins in the context of performing big data analysis on tons of commodity hardware.
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Introducing Apache Hadoop: The Modern Data Operating System
Eli Collins introduces Hadoop: why it came about, the benefits it produces, its history, its architecture, use cases and applications.
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Rewriting GitHub Pages with Riak and Webmachine
Jesse Newland discusses how GitHub pages were re-written with Erlang, Riak and Webmachine in order to improve their performance.
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Petabyte Scale Data at Facebook
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.
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Real World Redis
David Czarnecki discusses several Redis data structures and their associated libraries used in real cases for building leaderboards, relationships and activity feeds.
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Facebook News Feed: Social Data at Scale
Serkan Piantino discusses news feeds at Facebook: the basics, infrastructure used, how feed data is stored, and Centrifuge – a storage solution.
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Keynote: Spring 2012 and Beyond
Adrian Colyer, Juergen Hoeller, Mark Pollack and Graeme Rocher present SpringSource’s Unifying Component Model, current developments regarding Big Data, and betting on Grails.
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Eventually-Consistent Data Structures
Sean Cribbs discusses Convergent Replicated Data Types, data structures that tolerate eventual consistency.
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Embracing Concurrency at Scale
Justin Sheehy discusses designing reliable distributed systems that can scale in order to deal with concurrency problems and the tradeoffs required by such systems.
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