Department of Computer Science, SPMVV, Tirupathi, India
The development of Big Data is rapidly accelerating and affecting all areas of technologies by increasing the benefits for individuals and organizations. Big data can be categorized by its volume, variety and velocity. Since data size is bigger, it requires sophisticated techniques, tool and architectures to analyze the data. To extract knowledge from Big Data, various models, programs, softwares, hardwares and technologies have been designed and proposed. They try to ensure more accurate and reliable results for Big Data applications. In fact, many parameters should be considered: technological compatibility, deployment complexity, cost, efficiency, performance, reliability, support and security risks. This paper is a case study that review recent technologies developed for Big Data. It aims to help to select and adopt the right combination of different Big Data technologies according to their technological needs and specific applications’ requirements.
Big Data, deployment complexity, volume, variety, velocity
