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Oracle Big Data Appliance Product Family Expanded

Solutions help customers jumpstart initial big data projects, scale more cost-effectively.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Oracle today released Oracle Big Data Appliance X3-2 Starter Rack and Oracle Big Data Appliance X3-2 In-Rack Expansion.

Oracle Big Data Appliance X3-2 Starter Rack contains six Oracle Sun servers within a full-sized rack with redundant Infiniband switches and power distribution units; it enables customers to jumpstart their first Big Data projects with an optimally sized appliance.

Oracle Big Data Appliance X3-2 In-Rack Expansion includes a pack of six additional servers to expand the above configuration to 12 nodes and then to a full rack of 18 nodes and helps customers easily and cost-effectively scale their footprint as their data grows. 

Both new systems include the existing software stack for Oracle Big Data Appliance X3-2: Oracle Linux, Oracle Hotspot Java Virtual Machine, Cloudera's Distribution Including Apache Hadoop (CDH), Cloudera Manager, and Oracle NoSQL Database.  Integrating Hadoop into existing enterprises, Oracle also provides powerful SQL access to HDFS data. This enables organizations to leverage their existing Oracle SQL skill sets and tools to seamlessly query and analyze data stored in Hadoop.

Oracle Big Data Appliance X3-2 (full rack configuration) is now available through Oracle Infrastructure as a Service (IaaS), where organizations can obtain Oracle Big Data Appliance X3-2 on-premise, behind their firewall, for a monthly fee. With Oracle IaaS for Oracle Big Data Appliance, organizations can eliminate upfront capital expenditures for their big data needs.

The Oracle Big Data Appliance X3-2 product family is comprised of Engineered Systems that simplify the implementation and management of Big Data by integrating hardware and software to acquire, organize and analyze Big Data.

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