Comparative Study of Big Data Technologies and Frameworks - Tripathi, Mayank; Agarwal, A. K (International Journal of Computer Sciences and Engineering, 2025)
The organization's hunger for data insights and the adaptation of the World Wide Web has increased exponentially the generation and collection speed of data. There is a challenge to capture, store and analyze this large set of unstructured data, which have taken the shape of Big Data. In this paper, the definition of Big Data is introduced from different aspects to comprehend its concept. The architecture of Big Data is analyzed to study the processing mechanism of Big Data. The various Big Data technologies like Hadoop, HBase, Map Reduce, Pig, Hive, Sqoop, and Flume are studied and compare based on features supported by them. A comprehensive study of frameworks like Apache Spark, Cloudera, and Hortonworks used for execution of Big Data technologies is done by highlighting their important features. This paper also represents how data related to fields like the Stock market, Agriculture, Medical Health Records, and Internet traffic is stored, processed and analyzed using Big Data technologies and frameworks