Next Generation Infrastructure for Big Data - A Challenge | Original Article
The Internet has engender an explosion in data growth in the form of Data Sets, called Big Data that are so large they are difficult to store, manage, and canvass using traditional RDBMS which are tuned for Online Transaction Processing (OLTP) only. Not only is this new data heavily unstructured, voluminous and stream rapidly and difficult to tackle but even more importantly. The infrastructure cost of Hardware and Software required to crackle it using traditional RDBMS to drive any analytics or business intelligence online (OLAP) from it is prohibitive. To capitalize on the Big Data trend, a new maker of Big Data technologies (such as Hadoop, Google App Engine, Microsoft Azure and others) many combines have emerged which are leveraging new parallelized processing. Commodity hardware, open source software, and tools to capture and analyse these new data sets and provide a price/performance that is 10 times better than existing Data Warehouse/Business Intelligence system. This paper presents an overview of the cloud computing scenario today. It provides the advantages and disadvantages of cloud, different examples of the cloud services, different enterprises in the field of cloud computing are being mentioned in the paper.