Big data tools such as Cassandra and Hadoop are transforming how data is stored and exploited at scale. But without similarly capable search technologies, enterprise adopters face challenges when it comes to gaining insights from that data. Read more at GigaOM Pro »
Organizations are coping with the challenge of processing unprecedented volumes of data. However, the processes involved with using a large cluster to run applications like Hadoop are error-prone. So IT managers are turning to cluster-management solutions to automate tasks associated with cluster creation, management and maintenance. Read more at GigaOM Pro »
Big data has become the latest front for the patent troll epidemic as a shell company is suing firms for using a common software framework known as the Hadoop Distributed File System (HDFS). Read more »
DynamoDB, AWS’ latest effort to rock the technology establishment, has many implications for other players in the big data and cloud computing markets. A new GigaOM Pro research note examines just who is affected, and how. Read more at GigaOM Pro »
The fight for Hadoop dominance is officially on. While Hortonworks is busy answering questions about its product strategy, Cloudera and MapR will demonstrate new versions of their distributions overflowing with bells and whistles. And there are several other competitive products lurking in the background. Read more »
Hadoop is a very valuable tool, but it’s far from perfect. While Apache, Cloudera, EMC, MapR and Yahoo focus on core architectural issues, there is a group of vendors trying to make Hadoop a more-fulfilling experience by focusing on business-level concerns such as applications and utilization. Read more »
San Jose, Calif.-based storage startup MapR, which provides a high-performance alternative for the Hadoop Distributed File System, will serve as the storage component for EMC’s forthcoming Greenplum HD Enterprise Edition Hadoop distribution. Cloudera announced an HDFS partnership of its own with compression expert RainStor. Read more »
During an afternoon panel entitled “The Many Faces of MapReduce — Hadoop and Beyond,” moderator Gary Orenstein compared the two primary Hadoop components — MapReduce and the Hadoop Distributed File System — to the meat and bread of a sandwich. Read more »
