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Good Chart comparing four types of Data Stores: Key-Value, Tabular/Columnar, Document Store, Relational excerpt: The bottleneck is no longer around performance or the cost of computing - it's about quickly getting the information to thousands, or hundreds of thousands, of nodes trying to act as one computer delivering a service. Google and IBM both have written about the data center as a computer, and Facebook says it thinks of adding hardware at the rack level rather than at the server level. But the current means of storing and accessing data have not made this leap from a single server to a rack - let alone an entire data center. As programmers attempt this leap, they face several difficulties, which include working with existing software and programming languages and figuring out what problems and bottlenecks the new services built on these monolithic computer platforms will encounter. Plus, the IT world doesn't all move at once, which means plenty of jobs and workloads will continue with the old way of doing things - that is, relational databases such as Oracle's offerings and the open source MySQL, which Oracle now has a stake in thanks to its purchase of Sun. The result is not a steady movement to non-relational databases or other methods of storing data, but a back-and-forth as programmers and businesses figure out what kind of architecture they need and what problems they want to solve. For a closer look at the issue and a bunch of charts detailing how the landscape is currently laid out, analyst Matt Sarrel, has penned a report over at GigaOM Pro (sub. req'd.) on the NoSQL movement called "NoSQL Databases - Providing Extreme Scale and Flexibility."

Good run down of new big data technologies for Cloud Computing. The technologies are arranged in context beginning with Apache Hadoop and including HBase and MongoDb. Nice reference article.