Guide to NoSQL databases: How they can help users meet big data needs
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NoSQL databases are most easily defined by what they aren't -- reliant on Structured Query Language, or SQL. But...
what are NoSQL databases? Trading relational models for a distributed, schema-less data structure, NoSQL databases are highly scalable and have gained popularity riding a wave of massively parallel Web applications. There are many categories of NoSQL designs -- key value, graph, document-oriented -- and well-known technologies include BigTable, HBase, Cassandra, Couchbase, MongoDB and SimpleDB.
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Developers looking to build big Web applications needed to add more and more processing nodes to keep up with almost boundless demand for computing power. Relational databases came up short, so software engineers at Google, Amazon, Facebook and Yahoo devised non-SQL solutions -- laying the groundwork for big data analytics and expanded cloud computing services. Since 2009, a cavalry charge of NoSQL software startups entered the void with commercial products.
NoSQL is also known as "not only SQL," because some NoSQL databases do support SQL elements. But most don’t share key traits of relational databases like atomicity and consistency, so though NoSQL may help keep the auction chant going on eBay, it might break any bank using it for transaction processing. And with a ready pool of skilled developers, the incumbent relational database will hold on in most business applications.