The Storage And Analytics Potential Of HBase Over The Cloud: A Survey

TL;DR

This survey explores how HBase, a NoSQL database, is utilized in cloud environments to store and analyze large, complex biomedical data like biosignals, highlighting recent applications in healthcare analytics.

Contribution

It provides a comprehensive review of HBase's deployment in cloud-based biomedical data storage and analytics, emphasizing recent biomedical engineering applications.

Findings

HBase effectively manages large, heterogeneous biomedical data.

Cloud deployment enhances scalability and accessibility for biomedical analytics.

HBase supports offline biomedical data analysis workflows.

Abstract

Apache HBase, a mainstay of the emerging Hadoop ecosystem, is a NoSQL key-value and column family hybrid database which, unlike a traditional RDBMS, is intentionally designed to scalably host large, semistructured, and heterogeneous data. Prime examples of such data are biosignals which are characterized by large volume, high volatility, and inherent multidimensionality. This paper reviews how biomedical engineering has recently taken advantage of HBase, with an emphasis over cloud, in order to reliably host cardiovascular and respiratory time series. Moreover, the deployment of offline biomedical analytics over HBase is explored.