A double-sided dilemma Of course, for organizations considering life after Hadoop there were two central questions to answer: What do I do with my Hadoop Distributed File System (HDFS) data?

Doug Cutting, creator of the distributed computing platform Hadoop, on why the platform is in an almost unassailable position and what's in store for the platform.

One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they ...

Modern systems, such as Hadoop Distributed File System (HDFS), are primarily designed for large datasets and are often burdened by the metadata overhead when managing vast numbers of small files.

Hadoop 1.0 essentially provided an open source implementation of GFS—Hadoop Distributed File System (HDFS)—and an implementation of MapReduce. The Promise Hadoop was battle-hardened at Yahoo and, in ...

This paper is to discuss about two distributed file systems Google File System (GFS) and Hadoop Distributed File System (HDFS) and compare them by making various use of parameters.

Much has changed since the Hadoop project was originally released. This podcast reviews the latest trends in the world of Hadoop and distributed computing.

Hadoop is here to stay. But it's mature analytics tools for Hadoop, DBMS abstraction layers over it and Hadoop-as-a-Service cloud offerings that will make the open source Big Data platform actionable.

Big data can mean big threats to security, but BlueTalon just launched what it calls the first-ever filtering and dynamic masking capabilities for use directly on the Hadoop Distributed File ...