Ready to join the growing ranks of businesses (including a number of Fortune 500 companies) that are utilizing the power of Hadoop for big data analysis? Then you’ll want to be able to pick the right Hadoop vendor. There are a lot of companies out there promising the moon and stars, and many can truly deliver an enormous ROI on big data innovations. However, the right vendor for your applications isn’t necessarily the right one for another business. Unfortunately, with the growing demand for big data analytics, there are also some newcomers out there that can’t deliver what they promise. Here’s your guide to selecting the perfect vendor for your Hadoop plans. Continue Reading
Hadoop’s growth and media attention over the past few years pales in comparison only to the biggest tech news, like the advancement of cloud computing or the explosion of cellular technologies. But this past year marked a milestone for Hadoop, as the platform transitioned from something people wondered about into something people are actually using in meaningful and productive ways.
Hadoop turns mere data into powerful insight. And according to a survey by information technology research firm Gartner, 73 percent of all enterprises have invested or plan to invest in big data in the next two years. Continue Reading
Hadoop is a computing platform that makes big data easier to handle. How Hadoop stores files and processes data are the two most important characteristics of the platform. Hadoop allows you to store files that are bigger than what can be stored on a particular server. It also allows you to store large numbers of files. How Hadoop processes data is different from how we used to think about processing. Rather than moving data over a network to be processed, the Hadoop process called MapReduce moves the processing power to the data.
Once limited to internet giants like Google, Hadoop is moving into the business mainstream, allowing businesses to ingest and analyze massive quantities of structured and unstructured data. To realize its full data crunching capacity, Hadoop needs powerful infrastructure, and most companies don’t have the hardware necessary to set up Hadoop clusters on their premises.
But now providers offer tools that let businesses use Hadoop in the cloud. This is terrific for use case scenarios and for businesses where the ingestion and processing of data are unpredictable or intermittent. However, with Hadoop, input / output (I/O) demands are heavy, and virtualization tools can slow I/O down considerably. Hadoop is a great enabler, but for maximum performance, it needs to be run on bare metal rather than in a virtual environment.