Abstract
In the past years, Big Data has become a hot topic across several business areas. One of the main concerns regarding this concept is how to handle the massive volume and variety of data efficiently. Due to the notorious complexity of the data associated to the Big Data concept, usually motivated by data volume, efficient querying analysis mechanisms are mandatory for data analysis purposes. Motivated by the rapidly development of tools and frameworks for Big Data, there is much discussion about querying tools and, specifically, those more appropriated for specific analytical needs. This paper explores some of the available querying tools, describing and comparing their main characteristics and architectures, crucial knowledge for selecting the more appropriate ones for inclusion in a specific Big Data analytical architecture.
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Acknowledgments
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT (Fundação para a Ciência e Tecnologia) within the Project Scope: UID/CEC/00319/2013, and by Portugal Incentive System for Research and Technological Development, Project in co-promotion nº 002814/2015 (iFACTORY 2015-2018).
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Rodrigues, M., Santos, M.Y., Bernardino, J. (2017). Describing and Comparing Big Data Querying Tools. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-56535-4_12
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DOI: https://doi.org/10.1007/978-3-319-56535-4_12
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