May 21, 2012
Out-of-the-box blueprints for Twitter- and Facebook-like analytics systems available for download today
NEW YORK, May 21 — GigaSpaces Technologies, a pioneer of data scalability and next-generation application platforms for mission-critical applications, announces the launch of XAP 9.0. At the core of the latest release of the GigaSpaces platform is its ability to quickly launch a high-performance real-time analytics system for applications processing massive data sets, quickly and easily.
"In today's business world there is an increased – even dire – need for real-time insights, especially for large-scale location-aware mobile, social, and financial/risk analysis applications. This is clearly evidenced by the launch real-time analytics platforms by Facebook, Google, and Twitter this past year," says Adi Paz, GigaSpaces EVP of Marketing & Business Development. "What is common to all real-time analytics systems is the need for streaming data processing, alongside batch processing, such as Hadoop provides. However, building a system for Big Data apps is complicated – it must maintain reliability, scalability, and performance even at immensely large scales of data. XAP 9.0 was specifically designed to resolve these challenges."
Major social networking platforms like Facebook and Twitter have developed their own architectures for handling the need for real-time analytics on huge amounts of data. However, not every company has the need or resources to build their own Twitter-like solution. This is where XAP 9.0 comes in. With the GigaSpaces real-time analytics solution for Big Data, there is no need to reinvent the wheel – GigaSpaces has taken the same Twitter/Facebook-like blueprint, and made it simple enough for developers to implement a Big Data analytics system in a matter of days, or even less. GigaSpaces XAP has a long record of providing elastic real-time processing, and in version 9.0 these capabilities have been honed to specifically meet today's challenges to real-time analytics for Big Data.
What are the issues that make real-time analytics for Big Data such a challenge? These are the "3 Vs" of Big Data:
GigaSpaces XAP 9.0 includes the exact feature set to meet these challenges:
"What sets apart the GigaSpaces Big Data solution for real-time analytics is the combination of simplicity and reliable high performance," says Paz. "Real-time analytics is actually a very complex area, and the ability to get a ready-made, easy-to-implement solution cannot be overestimated. At the same time, simplicity is not enough for business that require accuracy, speed and reliability as basic requirements. XAP 9.0 provides all of the above."
Join us for our webinar and meetup on Big Data:
GigaSpaces Technologies is the pioneer of a new generation of application virtualization platforms and a leading provider of end-to-end scaling solutions for distributed, mission-critical application environments, and cloud enabling technologies. GigaSpaces is the only platform on the market that offers truly silo-free architecture, along with operational agility and openness, delivering enhanced efficiency, extreme performance and always-on availability. The GigaSpaces solutions are designed from the ground up to run on any cloud environment – private, public, or hybrid – and offer a pain-free, evolutionary path to meet tomorrow's IT challenges. Hundreds of organizations worldwide use GigaSpaces' technology to enhance IT efficiency and performance, among which are Fortune Global 500 companies, including top financial service enterprises, e-commerce companies, online gaming providers, and telecom carriers. For more information, visit http://www.gigaspaces.com, or the company's blog at http://blog.gigaspaces.com.
Source: GigaSpaces Technologies
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When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
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