Oracle Boosts Big Data Appliance, Adds Cloudera
Oracle gives a storage and Cloudera boost to its big data appliance, Alcatel-Lucent helps uncover mobile analytics, and CA ERwin bridges the big data gap in the enterprise.
November 13, 2013
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Oracle gives a storage and Cloudera boost to its big data appliance, Alcatel-Lucent helps uncover mobile analytics, and CA ERwin bridges the big data gap in the enterprise.
Oracle Boosts Big Data Appliance
Oracle (ORCL) announced that Big Data Appliance X4-2 is now available, providing enterprises with a comprehensive and secure engineered system optimized to run Cloudera’s entire Platform for Big Data, Cloudera Enterprise, at a low overall total cost of ownership. The new appliance includes the entire Cloudera Enterprise technology stack and 33 percent more storage capacity for a total of 864 terabytes per rack. Meeting diverse needs the appliance features Cloudera Distribution for Apache Hadoop, Oracle NoSQL Database, Cloudera Impala and Cloudera Search. Oracle also announced that it is a co-founder of the Apache Sentry project to deliver fine-grained authorization to data stored in Apache Hadoop. “Oracle Big Data Appliance X4-2 continues to raise the Big Data bar, offering the industry’s only comprehensive appliance for Hadoop to securely meet enterprise Big Data challenges,” said Çetin Özbütün, senior vice president, Data Warehousing and Big Data Technologies at Oracle. “Now that Oracle Big Data Appliance comes with the Entire Cloudera Enterprise Technology Stack and a significant increase in storage capacity, enterprises can build an even more cost-effective Big Data platform that can help generate new business value quickly and effectively.”
Mobile analytics enhanced by Alcatel-Lucent
Alcatel-Lucent (ALU) announced that its Motive Big Network Analytics solution is enhancing the way mobile operators capture data and extract intelligence from their networks. The new solution is the newest addition to its Ultra-Broadband portfolio, to help operators. The solution will allow them to better use their greatest asset – the network – and unlock not just data, but the intelligence to help them make future decisions. The Motive solution is comprised of Alcatel-Lucent's Wireless Network Guardian (WNG), its Kindsight Security Analytics, and its Big Network Analytics Data Miner. “Our Motive Big Network Analytics solution combines key characteristics of Big Data and mobile network analytics," said Andrew McDonald, President, IP Platforms Division at Alcatel-Lucent. "It allows service providers to internally leverage their greatest asset -- network data – to make better informed decisions about future deployments, service enhancements and network optimization. Leveraging this data complements operator Big Data projects by allowing them to more easily identify ‘sweet spots’ for market differentiation. In turn, it introduces more exciting services and a better experience for customers.”
CA ERwin bridges big data gap
CA Technologies (CA) announced a new release of CA ERwin CA ERwin Data Modeler, the company’s industry-leading solution for collaboratively visualizing and managing business data across the enterprise in support of data governance, Big Data analytics, business intelligence and other initiatives. The new r9.5 release includes support for Big Data technologies such as Apache Hadoop Hive, Cloudera and Google BigQuery, driving integration and a centralized view of both the traditional and newer data sources now impacting business decision-making. In addition, a new report designer in CA ERwin facilitates better visualization and sharing of information across the enterprise and among a broad range of both business and technical users. “Today there are entirely new, non-conventional sources of information, such as Big Data, that factor into the business analysis equation, but determining the relevance and relative value of a given data element is exceptionally difficult,” said Al Hilwa, program director, Application Development Software, IDC. “CA ERwin enables organizations to quickly and easily connect the dots between their disparate data sources, giving them meaningful context that is critical to the success of their data management efforts.”
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