@article{(Open Science Index):https://publications.waset.org/pdf/9999590,
	  title     = {Comparative Analysis of Diverse Collection of Big Data Analytics Tools},
	  author    = {S. Vidhya and  S. Sarumathi and  N. Shanthi},
	  country	= {},
	  institution	= {},
	  abstract     = {Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {8},
	  number    = {9},
	  year      = {2014},
	  pages     = {1646 - 1652},
	  ee        = {https://publications.waset.org/pdf/9999590},
	  url   	= {https://publications.waset.org/vol/93},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 93, 2014},
	}