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Operationalizing Analytics with NewSQL

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Software Engineering and Algorithms (CSOC 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 230))

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Abstract

Operational data and analytical data are no longer two separate disciplines and discussions. Data Analysis is gaining more ground and more request from companies that begin to base their strategies - as well as decision intelligence and decision management - on factual information. In surveying the state of the data industry and the trends in data management technologies, NewSQL systems appear to be more present. They are able to answer the question of bridging operational data storage and administration with providing real-time access to analytical data. This paper aims to provide a structured look into the features and capabilities offered by NewSQL systems that can be leveraged to allow Data Analysis over a variety of data types. Furthermore, it provides an overview of Realtime Analytics offerings, Map Reduce capabilities and hybrid (transactional and analytical) features.

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Acknowledgments

This research was made possible by funding from the ICT-AGRI-FOOD 2020 Joint Call. This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CCCDI - UEFISCDI, project number COFUND-ICT-AGRI-FOOD-MUSHNOMICS 205/2020, within PNCDI III.

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Authors and Affiliations

  1. Computers and Information Technology, Technical University Cluj Napoca, Cluj-Napoca, Romania

    Ionela Chereja, Sarah Myriam Lydia Hahn, Oliviu Matei & Anca Avram

Authors
  1. Ionela Chereja
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  2. Sarah Myriam Lydia Hahn
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  3. Oliviu Matei
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  4. Anca Avram
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Correspondence to Ionela Chereja .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Chereja, I., Hahn, S.M.L., Matei, O., Avram, A. (2021). Operationalizing Analytics with NewSQL. In: Silhavy, R. (eds) Software Engineering and Algorithms. CSOC 2021. Lecture Notes in Networks and Systems, vol 230. Springer, Cham. https://doi.org/10.1007/978-3-030-77442-4_21

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