InfoQ Homepage NoSQL Content on InfoQ
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MySQL to NoSQL: Data Modeling Challenges in Supporting Scalability
Kenneth M. Anderson shares some of the data modeling issues encountered while transitioning from a relational database to NoSQL.
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Apache Cassandra Anti Patterns
Matthew Dennis covers the most common mistakes made with Cassandra that he has noticed being made both in deployment and code.
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Transactions: Over Used or Just Misunderstood?
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.
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Data Modeling with Graphs
Peter Bell presents several patterns for modeling and retrieving data from graph databases using Neo4j in his examples.
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Ten Reasons Why You Should Use a Graph Database For Your CMS
Axel Morgner compares different open source CMS’s and outlines the benefits of implementing one using a graph database.
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The Evolving Panorama of Data
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.
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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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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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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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