Oracle Debuts Big Data Appliance X3-2 and Updated Hadoop Connectors
Oracle announces new, high-performance server hardware and software offerings that play well with the popular Hadoop Big Data platform.
Oracle today unveiled Big Data Appliance X3-2, a combined server hardware and software offering that the company is pitching to businesses as a cost-effective and simplified alternative to piecing together their own Big Data processing platforms.
On the hardware front, the Oracle Big Data Appliance portfolio is getting a big performance boost, beginning with the availability of Intel's latest server processors. The new systems feature 8-core Intel Xeon E5-2600 chips, resulting in 33 percent more processing power (36 processors, 288 CPU cores) than its predecessor in an 18 compute and storage server configuration with 648 TB storage.
Oracle also boasts that customers can expect 33 percent more memory per node with 1.1 TB of main memory and a smaller energy bill to boot. Thanks to more energy efficient internals, the system slashes power and cooling requirements by up to 30 percent.
In terms of software, Big Data Appliance X3-2 offers support for Cloudera Distribution of Apache Hadoop, including NameNode High Availability in Hadoop to help make Hadoop clusters less prone to failure. The system also includes Oracle NoSQL Database Community Edition 2.0 with improved Hadoop integration and the Oracle Enterprise Manager plug-in for Big Data Appliance.
Big Data Appliance X3-2 also ships with updated distributions of Oracle Linux, Oracle Java Development Kit and open source R, the latter of which has been "optimized to work with high performance multi-threaded math libraries," says Oracle.
The company is also rolling out new Oracle Big Data Connectors to provide tighter integration between Hadoop and Oracle's Big Data products, namely Oracle Database, Oracle Data Integrator and Oracle R Distribution.
They include the Oracle SQL Connector for Hadoop Distributed File System for SQL queries on Hadoop data from Oracle Database. The updates also provide "transparent access to the Hive Query language from R and introduction of new analytic techniques executing natively in Hadoop," according to the company.
All told, the upgrades are meant to help organizations manage and draw useful insights from the vast stores of information sitting in their data warehouses. It's a job that's getting tougher as businesses are continually deluged with data.
"An influx of raw datasets are flooding every enterprise. However, before businesses can take advantage of the potential opportunity, they face a significant challenge in organizing these diverse data sources," said Cetin Ozbutun, vice president of Data Warehousing and Big Data Technologies for Oracle in a statement. "The latest updates further improve the abilities of our customers to optimize big data workloads and integrate them with their data warehouses to easily analyze all data throughout the enterprise."