arXiv (Cornell University) · 2013 · 369 citations · 17 references
ComputingComputer ScienceBig Data AnalyticsData ManagementDatabasesData Storage SystemsData WarehousingDatabase ManagementDistributed DatabasesNosql DatabasesQuery ProcessingBig Data Analytics ArchitectureBig Data ClassificationDatabase Management SystemsKey-value StoresNewsql DatabasesRelational Database SystemsScalable Data Management
Digital growth has produced terabyte‑to‑petabyte volumes of structured, unstructured, and hybrid data that conventional relational databases cannot manage efficiently. The paper aims to classify, describe characteristics, and evaluate NoSQL databases for big‑data analytics. It proposes complementing traditional RDBMS with alternative systems such as NoSQL, NewSQL, and search‑based databases. The resulting report provides organizations with an independent assessment of the strengths and weaknesses of various NoSQL approaches for handling massive data volumes.
Digital world is growing very fast and become more complex in the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), velocity (high speed in growth) in nature. This refers to as Big Data that is a global phenomenon. This is typically considered to be a data collection that has grown so large it can not be effectively managed or exploited using conventional data management tools: e.g., classic relational database management systems (RDBMS) or conventional search engines. To handle this problem, traditional RDBMS are complemented by specifically designed a rich set of alternative DBMS; such as - NoSQL, NewSQL and Search-based systems. This paper motivation is to provide - classification, characteristics and evaluation of NoSQL databases in Big Data Analytics. This report is intended to help users, especially to the organizations to obtain an independent understanding of the strengths and weaknesses of various NoSQL database approaches to supporting applications that process huge volumes of data.
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Business, Information Systems, Management Information Systems +17