An Architecture for the Development of Distributed Analytics Based on Polystore Events

TY - GEN

T1 - An Architecture for the Development of Distributed Analytics Based on Polystore Events

AU - Zolotas, Athanasios

AU - Barmpis, Konstantinos

AU - Medhat, Fady

AU - Neubauer, Patrick

AU - Kolovos, Dimitris

AU - Paige, Richard F.

N1 - 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. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

PY - 2021/3/4

Y1 - 2021/3/4

N2 - 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.

AB - 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.

KW - Analytics

KW - Hybrid databases

KW - Polystores

KW - Queries

UR - http://www.scopus.com/inward/record.url?scp=85103549622&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-71055-2_5

DO - 10.1007/978-3-030-71055-2_5

M3 - Conference contribution

AN - SCOPUS:85103549622

SN - 9783030710545

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 54

EP - 65

BT - Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2020 and DMAH 2020, Revised Selected Papers

A2 - Gadepally, Vijay

A2 - Mattson, Timothy

A2 - Stonebraker, Michael

A2 - Kraska, Tim

A2 - Wang, Fusheng

A2 - Luo, Gang

A2 - Kong, Jun

A2 - Dubovitskaya, Alevtina

PB - Springer

T2 - VLDB workshops: International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020

Y2 - 31 August 2020 through 4 September 2020

ER -