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.
|Title of host publication||Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2020 and DMAH 2020, Revised Selected Papers|
|Editors||Vijay Gadepally, Timothy Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya|
|Number of pages||12|
|Publication status||Published - 4 Mar 2021|
|Event||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 - Virtual, Online|
Duration: 31 Aug 2020 → 4 Sept 2020
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||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|
|Period||31/08/20 → 4/09/20|
Bibliographical noteFunding Information:
Acknowledgements. This work is funded by the TYPHON project (#780251).
This work is funded by the European Union Horizon 2020 TYPHON project (#780251).
© 2021, Springer Nature Switzerland AG.
- Hybrid databases