Big Data in Cloud Environment - Sharma, Poornima; Garg, Varun; Kaur, Randeep; Sonare, Satendra (International Journal of Computer Sciences and Engineering, 2013)
Big Data concerns large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data is now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. However, big data entails a huge commitment of hardware and processing resources, making adoption costs of big data technology prohibitive to small and medium sized businesses. Cloud computing offers the promise of big data implementation to small and medium sized businesses. Big Data processing is performed through a programming paradigm known as MapReduce. Typically, implementation of the MapReduce paradigm requires networked attached storage and parallel processing. The computing needs of MapReduce programming are often beyond what small and medium sized business are able to commit. Cloud computing is on-demand network access to computing resources, provided by an outside entity. Common deployment models for cloud computing include platform as a service (PaaS), software as a service (SaaS), infrastructure as a service (IaaS) & hardware as a service (HaaS).