As research and adoption shows, Hadoop is the big data technology solution of the future. We have conducted extensive market research to evaluate the relative strengths and weaknesses of selected commercial Hadoop vendors. As part of this research study, the following nine vendors were selected as participants: Hortonworks, IBM, Intel, Amazon Web Services (AWS), Cloudera, Microsoft, Pivotal Software, Teradata, and MapR Technologies. After applying a 32-criteria evaluation checklist, Forrester rated these vendors in relation to each other.
Hadoop gaining ground
Hadoops distributed storage architecture and parallel processing framework has gained immense popularity among both large and small enterprises. Hadoop is a technology that enhances big data storage and processing power at high speed and it is unmatched by competing technologies. The cherry on top being that an open-source version is available for those who wish to start modestly.
Hadoop today stands for a catch-all technology solution that promises open source, low-cost storage systems, tremendous scaleability, and super fast big data analytics with low-cost servers. According to one analyst:
A distributed data platform that includes, extends, and augments Apache Hadoop (Common, HDFS, YARN, MapReduce) as a core component of the solution, supports Hadoop-related projects, and adds differentiated features that make it attractive to enterprises.
Enterprises who must deal with massive piles of unstructured and binary data must embrace Hadoop as this is currently the only data platform that offers tremendous flexibility in manipulating data or any size, type, or structure. The vendors engaged in deploying commercial Hadoop extend and augment capabilities of Hadoop, then add differentiated features to stand out in the crowd.
When we think of commercial grade Hadoop solutions, there are nine top vendors. The chart below shows how they are positioned in relation to one another. The whole exercise has been targeted to help technology management professionals derive the appropriate Hadoop solution for specific business needs.
Big Data Hadoop Solutions Q1 14
Hadoop as big data solution enabler
As businesses continue to seek insights hidden in vast repositories of structured, semi-structured, unstructured, Hadoop is available to:
Capture and store all types and sized of data
In the age of big data, without proper technologies and analytics tools, only 12% of the generated data can be used for analytics; the rest are wasted. Data that appears irrelevant now, such as mobile GPS data, might be a gold mine in the future. Hadoop enables enterprises to capture, store, and analyze high volumes of data without much fuss.
Enable easy and fast sharing of customer data
Today, big data drives every business function such as research and development, sales, advertising and marketing, or customer experience. In this scenario, if data sits quietly in silos, it gets very difficult to share that data across the organization. Hadoop provides technology to create a data lake, which is simply an integrated data repository containing data from combined, internal and external sources.
Provision advanced analytics
The modern visualization tools and predictive analytics techniques have made it possible to extract the last drop of insight or hidden patterns from big data. Hadoop not only supports large volumes of data but it also provisions matching processing power to execute high-end, statistical and machine-learning algorithms, meant for advanced big-data analytics.
As data sources continue to expand, Hadoop will appropriately scale to accommodate the volume, velocity, or variety of new datasets.
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