SURVEY PAPER ON BIG DATA PROCESSING AND TECHNOLOGIES

Big data is data sets that are so voluminous and complex that traditional data-processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. It is at the centre of a growing ecosystem of big data technologies that are primarily used to support advanced analytics initiatives, including predictive analytics, data mining and machine learning applications. Hadoop can handle various forms of structured and unstructured data, giving users more flexibility for collecting, processing and analyzing data than relational databases and data warehouses provide.

This paper introduced different technologies like Hadoop, Map Reduce, Hive, Hbase, Distributed Data, Relational Database, and NoSql.