According to research, generally, 2.5 quintillion bytes of data are produced every day. About 90% of the world’s data has been produced in the last two years alone. The amount of data is increasing immensely. There is a fight to use and store this tremendous information effectively. HBase is the top option for storing huge data. HBase has been selected for several purposes, including its scalability, efficiency, strong consistency support, and the capacity to support a broad range of data models. This paper seeks to define, taxonomically classify, and systematically compare existing research on a broad range of storage technologies, methods, and data models based on HBase storage architecture’s symmetry. We perform a systematic literature review on a number of published works proposed for HBase storage architecture. This research synthesis results in a knowledge base that helps understand which big data storage method is an effective one.

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