• Jyoti Haweliya
• Sourabh Choudhary
• Manish Hate

Now a day the term big data has become universal. In various arrears like an industry, academia, media etc. there is no single unified definition of Big Data, and various stakeholders provide different and often contradictory definition of Big Data. It is the term for any collection of data sets so large and very complex that it becomes hard to process using traditional data processing applications. There are so many challenges in front of this era for big data which includes analysis, curation, capture, sharing, search, transfer, storage, visualization, and the most important privacy violations. In this paper, we review various hardware platforms, technologies and their suitability for the Big Data environment. Basically, big data deals with huge parallel software running on not only tens, hundreds even thousands of servers that’s why the traditional relational database management system is not appropriate for it. Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.

Big data, Hadoop, IBM Infosphere, and Apache

"A SURVEY ON BIG DATA ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.558-561, September-2018, Available :http://www.jetir.org/papers/JETIR1809587.pdf

"A SURVEY ON BIG DATA ANALYTICS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp558-561, September-2018, Available at : http://www.jetir.org/papers/JETIR1809587.pdf