snydeq writes: "Facebook has said that it will soon open source Prism, an internal project that supports geographically distributed Hadoop data stores, thereby removing the limits on Hadoop's capacity to crunch data. 'The problem is that Hadoop must confine data to one physical data center location. Although Hadoop is a batch processing system, it's tightly coupled, and it will not tolerate more than a few milliseconds delay among servers in a Hadoop cluster. With Prism, a logical abstraction layer is added so that a Hadoop cluster can run across multiple data centers, effectively removing limits on capacity.'"
snydeq writes: "InfoWorld's Peter Wayner provides a round-up of seven tools aimed at extracting value from 'big data,' including reporting, analysis, visualization, integration, and development tools. 'The tools for tackling big data are just beginning to package the distributed computing power of Hadoop in a way that's a bit easier to use. Many of the big data tools are also working with NoSQL data stores,' Wayner writes. 'The biggest challenge may be dealing with the expectations built up by the major motion picture "Moneyball." All the bosses have seen it and absorbed the message that some clever statistics can turn a small-budget team into a World Series winner.'"
snydeq writes: "InfoWorld's Peter Wayner takes an in-depth look at four commercial Hadoop distributions aimed at businesses looking to process 'big data,' including clusters from Amazon, Cloudera, IBM, and MapR. 'There's no easy way to summarize the quickly shifting space. Each of these companies is pointed in a slightly different direction. They may all agree that the Hadoop collection of software is a great way to spread out work over a cluster, but they each have different visions of who would want to do this and, more important, how to accomplish it. The similarities are fewer than you might expect.'"
snydeq writes: "InfoWorld's Frank Ohlhorst discusses how virtualization, commodity hardware, and 'Big Data' tools like Hadoop are enabling IT organizations to mine vast volumes of corporate and external data — a trend fueled increasingly by companies' desire to finally unlock critical insights from thus far largely untapped data stores. 'As costs fall and companies think of new ways to correlate data, Big Data analytics will become more commonplace, perhaps providing the growth mechanism for a small company to become a large one. Consider that Google, Yahoo, and Facebook were all once small companies that leveraged their data and understanding of the relationships in that data to grow significantly. It's no accident that many of the underpinnings of Big Data came from the methods these very businesses developed. But today, these methods are widely available through Hadoop and other tools for enterprises such as yours.'"