Abstract
In recent years, big data is huge amount of data to uncover hidden attributes. Today’s technologies has possible to analyze the data and get data is almost immediately. Why big data is very important? Because cost reduction, faster, and better decision making using Hadoop. For example a large warehouse of terabytes of data is generated daily from social media’s like Twitter, LinkedIn and Facebook are case of organization in the people to people communication area for big data. Big data has 3 most important challenges of Volume, Variety, and Velocity. In this paper we have studied about the performance of Traditional Distributed File System (TDFS) and Hadoop Distributed File System (HDFS). Benefits of HDFS has support for flume tool in Hadoop comparing with TDFS. Memory block size data retrieving time and security are used as metrics in evaluating the performance of TDFS and HDFS. Result shows HDFC performs better than TDFS in the above metrics and HDFS is more suitable for big data analysis comparing of TDFS.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Recent Technology and Engineering (IJRTE)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
