Scientific and Commercial computing is undergoing an immense change with increasing demands for processing of large-scale datasets for a variety of needs such as simulation, modeling, and calculations of multivariate equations. Computation has largely been used as a method for achieving the results and is now shifting to a data intensive computing model to accomplish some of the most demanding scientific and commercial challenges in existence. Enterprise and commercial industries are experiencing the need to process increasingly large datasets for industries such as Oil & Gas, Communications, Media & Entertainment, Healthcare and Life Sciences and Big Data Analytics. Current data and storage architectures are not sufficient to provide for Terascale and Petascale Data Intensive Computing models and simulations which will require new flexible ways of data access at multi-terabyte per second speeds. Elastic cloud computing based access models is increasingly necessary to provide the economies of scale of shared infrastructure. An architectural framework is proposed for data intensive cloud computing based applications called Datalanx.