Abstract
As the capacity of main memory is growing, in-memory based big data analytics is becoming more popular. In-memory technologies support interactive analysis by providing high I/O throughput. On traditional high performance computing (HPC), big data processing needs data-intensive as well as computation-intensive systems for large data storage and high speed processing respectively. Currently, there are many such tools and technologies available which supports memory centric data processing to perform analysis on them. Taking advantage of in-memory on a HPC platform can result in a high speed, more reliable and fault tolerant data analysis. In this paper, we survey the existing storage and computation engines to perform big data analysis, and their performance while integrating together. Also, we discuss the contribution of such infrastructures in solving many I/O intensive analytical issues.
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