why hadoop for big data?
DESCRIPTION
Working with Big Data by using traditional relational databases and thousands of enormously expensive servers is no longer the best option. Here comes Apache Hadoop – a reliable open source technology that enables high-performance processing of huge amounts of data. It is an excellent solution to run large, scalable, distributed computations.TRANSCRIPT
©2014 by EliNext Group
Why Hadoop for Big Data
Nowadays, digital data is growing exponentially. Proliferation of
its volume, variety and velocity is known as the Big Data
phenomenon. Big Data includes large, diverse, complex,
structured, semi-structured and unstructured datasets
generated through software systems, collaboration tools, social
networking, video streams, payment transactions, sensors and
all other possible digital sources.
©2014 by EliNext Group
Obviously, those companies and organizations that are best
able to leverage Big Data for making well-timed and well-aimed
business decisions are expected to prosper in the near and
distant future. The challenge here lies in finding the most
efficient ways to manage, analyze, visualize and create new
value from terabytes and even petabytes of information in real
time.
Working with Big Data by using traditional relational databases
and thousands of enormously expensive servers is no longer
the best option. Here comes Apache Hadoop – a reliable open
source technology that enables high-performance processing of
huge amounts of data. It is an excellent solution to run large,
scalable, distributed computations.
Hadoop's file system (HDFS) is different from other distributed
file systems. HDFS creates multiple replicas of data blocks and
distributes them on compute nodes throughout a cluster in
order to ensure extremely rapid computations. The file system
©2014 by EliNext Group
is very fault-tolerant and is designed to be deployed on low-
cost hardware.
It is also due to Hadoop MapReduce software framework that
allows easy writing of applications for processing vast amounts
of data (multi-terabyte datasets) in-parallel on large clusters of
commodity hardware.
A wide variety of enterprises and organizations use Hadoop for
both research and production. According to IDC, revenues for
the worldwide Hadoop-MapReduce ecosystem software market
are expected to grow to $812.8 million in 2016 from $77 million
in 2011.
Recognizing the tremendous value of Hadoop for Big Data
processing and analytics, many companies invest time and
resources in this technology, seeing this as a necessary step
towards a sustainable development of their businesses. Some
of the notable users of Hadoop include Amazon.com, American
Airlines, Apple, eBay, Facebook, Hewlett-Packard, IBM,
©2014 by EliNext Group
LinkedIn, Microsoft, Twitter, Yahoo!.
Industries and Technology Areas:
Industries: software development
Technology Areas: Hadoop, HDFS, MapReduce, Big Data
©2014 by EliNext Group
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©2014 by EliNext Group
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Suggested citation: EliNext Group.2014. “Why Hadoop for Big Data”
<http://www.elinext.com/why-hadoop-for-big-data>
