Database Reference
In-Depth Information
platforms, leading to scale-out options and expanded situational awareness.
QRadar was very compelling as a stand-alone technology, but when com-
bined with Big Data, we're doing never-before-possible things to help lock
down our enterprise customers' domains.
IBM
i2 Intelligence Analysis Platform
IBM i2 provides an extensible, service-oriented environment that is designed
to integrate with your existing enterprise infrastructure. This platform facili-
tates and supports operational analysis, improves situational awareness, and
delivers faster, more informed decision making across and within organiza-
tions. Since the acquisition, IBM has been busy integrating the i2 platform
with the IBM Big Data platform, and extending the data that i2 end users can
discover and explore. i2's highly visual and intuitive end-user analytics help
you to identify and explore patterns, and then take action in rapidly evolving
environments.
Platform Symphony MapReduce
In 2011, IBM acquired Platform Computing, including their Platform Sympho-
ny MapReduce technology: a Hadoop-inspired run time specifically designed
for applications that require low-latency or sophisticated scheduling logic
across many simultaneous short-running jobs. BigInsights is the lead IBM
product offering for Hadoop, and Platform Symphony is considered to be a
complementary component of that offering.
What's interesting is the integration work that's been done for these prod-
ucts. For example, BigInsights can leverage Platform Symphony MapReduce as
the low-latency distributed run-time component running on its own cluster.
This enables customers who have specific low-latency or heavy computational
workloads to leverage this technology as part of a BigInsights deployment.
BigInsights may be deployed on one or more instances within a Platform Com-
puting grid, thereby leveraging its technical computing capabilities that support
heterogeneous applications. Existing Platform Symphony customers (of which
there are many) can add BigInsights to their existing grid and manage multiple
types of workloads across a common pool of resources. This eliminates the need
to set up a separate grid environment for BigInsights, and supports the sharing
of resources across both compute- and data-intensive applications.
