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Big Data is defined as high volume of variety of data with an exponentialdata growth rate. Data are amalgamated to generate revenue, which results alarge data silo. Data are the oils of modern IT industries. Therefore, the dataare growing at an exponential pace. The access mechanism of these data silosare defined by metadata. The metadata are decoupled from data server forvarious beneficial reasons. For instance, ease of maintenance. The metadata arestored in metadata server (MDS). Therefore, the study on the MDS is mandatoryin designing of a large scale storage system. The MDS requires many parametersto augment with its architecture. The architecture of MDS depends on the demandof the storage system's requirements. Thus, MDS is categorized in various waysdepending on the underlying architecture and design methodology. The articlesurveys on the various kinds of MDS architecture, designs, and methodologies.This article emphasizes on clustered MDS (cMDS) and the reports are preparedbased on a) Bloom filter$-$based MDS, b) Client$-$funded MDS, c) Geo$-$awareMDS, d) Cache$-$aware MDS, e) Load$-$aware MDS, f) Hash$-$based MDS, and g)Tree$-$based MDS. Additionally, the article presents the issues and challengesof MDS for mammoth sized data.

A Survey on Large Scale Metadata Server for Big Data Storage