For large-scale analytics, a distributed file system is kind of important. Even if you’re using Spark you need to pull a lot of data into memory very quickly. Having a file system that supports high ...

Cloud computing is a new technology which comes from distributed computing, parallel computing, grid computing and other computing technologies. In cloud computing, the data storage and computing are ...

Big data can mean big threats to security, thanks to the tempting volumes of information that may sit waiting for hackers to peruse. BlueTalon hopes to tackle that problem with what it calls the first ...

Facebook deployed Raid in large Hadoop Distributed File System (HDFS) clusters last year, to increase capacity by tens of petabytes, as well as to reduce data replication. But the engineering team ...

As the undisputed pioneer of big data, Google established most of the key technologies underlying Hadoop and many of the NoSQL databases. The Google File System (GFS) allowed clusters of commodity ...

LinkedIn engineers have open sourced a homegrown Big Data scale testing tool following a "crisis" they experienced after adding 500 machines to a Hadoop Distributed File System (HDFS) cluster, ...

MapR's file system was its original differentiator in the Hadoop market: unlike standard HDFS, which is optimized for reading, and supports writing to a file only once, MapR-FS fully supports the read ...

What are some of the cool things in the 2.0 release of Hadoop? To start, how about a revamped MapReduce? And what would you think of a high availability (HA) implementation of the Hadoop Distributed ...

As a poster child for big data, Hadoop is continually brought out as the reference architecture for big data analytics. But what exactly is Hadoop and what are the key points of Hadoop storage ...

Many of the major advances in HPC have been the result of collaboration between academia and the big government labs. This has been the case with PVFS (Parallel Virtual File System) and its latest ...