Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Title of host publication | Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2020 and DMAH 2020, Revised Selected Papers |
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Date | Published - 4 Mar 2021 |
Pages | 54-65 |
Number of pages | 12 |
Publisher | Springer Science and Business Media Deutschland GmbH |
Editors | Vijay Gadepally, Timothy Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya |
Original language | English |
ISBN (Print) | 9783030710545 |
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12633 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
To balance the requirements for data consistency and availability, organisations increasingly migrate towards hybrid data persistence architectures (called polystores throughout this paper) comprising both relational and NoSQL databases. The EC-funded H2020 TYPHON project offers facilities for designing and deploying such polystores, otherwise a complex, technically challenging and error-prone task. In addition, it is nowadays increasingly important for organisations to be able to extract business intelligence by monitoring data stored in polystores. In this paper, we propose a novel approach that facilitates the extraction of analytics in a distributed manner by monitoring polystore queries as these arrive for execution. Beyond the analytics architecture, we presented a pre-execution authorisation mechanism. We also report on preliminary scalability evaluation experiments which demonstrate the linear scalability of the proposed architecture.
Funding Information:
Acknowledgements. This work is funded by the TYPHON project (#780251).
Funding Information:
This work is funded by the European Union Horizon 2020 TYPHON project (#780251).
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
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