HP Vertica 6.1 Boosts Big Data Value
ASIA PACIFIC, 5 December 2012 — HP today announced HP Vertica Analytics Platform 6.1, a new version of its next-generation analytics platform, purpose built to simplify Big Data. The platform enables enterprises to optimize and monetize Big Data with analytics packs, performance enhancements, enhanced integration with Hadoop and simplified Amazon EC2 cloud deployments.
Businesses and governments recognize the value to be extracted from “Big Data”—mountains of data piling up from a number of disparate data sources, including traditional structured operational systems, unstructured data consisting of user data, social networking sentiment and semistructured data generated by machines and sensors.
The HP Vertica Analytics Platform is purpose built for organizations of all sizes to monetize Big Data at hyperspeed and massive scale. The HP Vertica Analytics Platform 6.1 expands data management options to manage and optimize Big Data with a Hadoop Distributed File System (HDFS) connector that speeds data loading by four times or more compared to the previous connector version in the HP Vertica Analytics Platform 6.0.(1)
The connector ensures seamless native integration between HDFS and the HP Vertica Analytics Platform, without requiring any resource-intensive MapReduce coding. This native integration allows clients to federate analytics queries across the HP Vertica Analytics Platform and Hadoop, ensuring high-performance analytics in a simple and scalable manner.
Better integration with Hadoop allows customers to gain insights from Big Data faster, whether the data is loaded directly into the HP Vertica Analytics Platform or is stored in Hadoop and analyzed via the HP Vertica Analytics Platform. The connector also ensures that a broad set of business intelligence (BI) tools can operate on Hadoop through the HP Vertica Analytics Platform.
In addition, the HP Vertica Analytics Platform 6.1 enables clients to:
- Optimize storage and simplify data archiving with flexible storage tiering that effectively uses existing storage media and archived data for offline storage rather than creating unnecessary backups;
- Quickly gain insights from information with a prebuilt R language pack that shortens the time for data scientists to begin performing advanced analytics, using one of the most popular open-source statistics packages in the market today;
- Achieve a faster return on information with expanded and improved performance of SQL functions for faster analytics;
- Simplify cloud deployments with a hardware virtual machine (HVM) based Amazon Machine Image (AMI) that includes Cloud Scripts for agile cluster management of Amazon EC2 deployments; and
- Streamline administration with tools to validate deployments, role-based access control to improve data and system security, as well as software development kit (SDK) extensions to ease the upgrade process.
“Organizations of all sizes are looking for ways to optimize and monetize Big Data, without sacrificing speed or choice,” said Narinder Kapoor, vice president and general manager, Enterprise Group, South East Asia, HP. “With this new release, our clients can rely on the HP Vertica Analytics Platform to solve their most challenging and business-critical Big Data initiatives with fast performance, massive scalability and openness to all types of information.”
Pricing and availability
HP Vertica Analytics Platform 6.1 is available immediately worldwide. Additional information about the software, and how to download a trial or purchase it, is available at http://my.vertica.com/evaluate.
- Based on internal performance benchmarks.
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© 2012 Hewlett-Packard Asia Pacific Pte Ltd. Registration No.: 198703164G. The information contained herein is subject to change without notice. The only warranties for HP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HP shall not be liable for technical or editorial errors or omissions contained herein.