Database Reference
In-Depth Information
IBM is driving its commitment to Big Data and analytics through sustained
investments and strategic acquisitions. In 2011, IBM committed a $100 million
investment in the research and development of services and solutions that
facilitate Big Data analytics. Look around the Big Data space. How many
vendors have spent over $16 billion (as of the time this topic was written—
like Big Data numbers, it's out of date by the time you are reading this, and
moving up), across 30 analytics-based acquisitions, in the last five years?
We often find people equating Big Data with Hadoop, and quite frankly
it's a huge mistake to think that way. Hadoop is one of many technologies
that is purpose-built for specific tasks. The value in Big Data (what your C-level
executive branch really cares about) revolves around
how it can be monetized.
It's great to store 1PB of data, but if you can't analyze it, what do you have?
A lot of data. Big Data is about analytics, and no other vendor is strategically
investing in analytics like IBM. IBM's two most recent acquisitions, Netezza
(whose main appliance has been rebranded as the IBM PureData System for
Analytics) and Vivisimo (whose products have been rebranded as InfoSphere
Data Explorer), had developed market-leading innovative technologies that
have now been integrated into the IBM Big Data platform. IBM also has the
largest commercial research organization on earth: hundreds of mathemati-
cians and data scientists developing leading-edge analytics. Finally, IBM has
the largest patent portfolio in the world, almost exceeding the combined total
of the next four biggest patent-receiving companies!
Many of the research themes and innovations that pertain to unstructured
data management, text analytics, image feature extraction, large-scale data
processing have been incorporated into IBM's Big Data platform. To be frank,
when you consider the strategic alignments around Big Data, there aren't
many other organizations in the world that are capable of delivering a compre-
hensive end-to-end Big Data platform like IBM.
2. Strong Commitment to Open Source Efforts
and a Fostering of Ecosystem Development
The open source community has been a major driving force for innovation in
Big Data technologies. The most notable of these is Hadoop, a software frame-
work that enables the processing of data-intensive computational tasks, in par-
allel and at scale. The Hadoop ecosystem consists of other related open source
projects that provide supporting utilities and tools. These projects provide
