Mortar Data, founded in 2010, creates a private, on-demand Hadoop cluster for clients' big data projects and creates "optimized jobs for execution" using Pig and Python. Amazon's S3 cloud storage ...

For example, the phrase “big data” has been so widely and poorly applied that the term has become almost meaningless. Nevertheless, beneath the hype of big data there is a real revolution in progress, ...

Hadoop and MapReduce have long been mainstays of the big data movement, but some companies now need new and faster ways to extract business value from massive -- and constantly growing -- datasets.

Fortunately, there are alternatives to Hadoop when it comes to big data projects. While not applicable to all situations, I've found that a Hadoop alternative can save time, money and slash risk.

Hadoop on Windows, or on Azure, could speed adoption of big data analytics by making access and analytics using familiar Microsoft tools, more widely available.

NEWS ANALYSIS: Apache Hadoop is opening up lots of possibilities for analyzing big data, but there is also complexity in the applications and techniques for managing that data effectively.

Because big data is much more than Hadoop and its ecosystem. For example, though the media has equated big data with Hadoop for years, data scientists have not.

Hadoop’s MapReduce provided folks with a big step in capability. It’s hard to overstate exactly how critical this commodification of big data has been for the world.

In the big data battle for architectural supremacy, the cloud is clearly winning and Hadoop is clearly losing. Customers are shying away from investing in monolithic Hadoop clusters in favor of more ...

Applications built on Hadoop can store and analyse multiple data streams and help, for example, regional bank managers control new account risk in their branches. They can match banker decisions with ...