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With the promise on-demand compute/storage resources, many users are deploying data-intensive scientific applications onto Clouds. To accelerate these applications, the prospect of caching intermediate data using the elastic compute and storage framework has proved promising. To this end, we believe that an in-depth study of cache placement decisions over various Cloud storage options would be highly beneficial to a large class of users. While tangential analyses have been proposed, ours in contrast focuses on cost-performance tradeoffs of maintaining a data cache with various parameters of any Cloud application. We have compared several Amazon Web Service (AWS Cloud) resources as possible cache placements and found that application dependent attributes like unit-data size, total cache size, and persistence, have far reaching implications on the cost of cache sustenance. Moreover, while instance-based caches expectedly yield higher cost, the performance that they afford may outweigh lower cost options.