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NoDA: Unified NoSQL Data Access Operators for Mobility Data

Published: 19 August 2019 Publication History

Abstract

In this paper, we propose NoDA, an abstraction layer consisting of spatio-temporal data access operators, which is used to access NoSQL storage engines in a unified way. NoDA alleviates the burden from big data developers of learning the query language of each NoSQL store, and offers a unified view of the underlying NoSQL store. Our approach is inspired by the equivalent paradigm of drivers (such as JDBC) in the relational database world, where the application code is indifferent to the exact underlying database engine. Still, the challenges in the NoSQL world are manifold, because of the lack of standardization in data access. We focus on the specific case of mobility data, and show how spatial and spatio-temporal operators, such as range queries and k-nearest neighbor, are supported in a unified way. Moreover, we present challenges and solutions for supporting spatial and spatio-temporal data in NoSQL stores.

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Cited By

View all
  • (2024)Technological and Research Challenges in Data Engineering for Sustainable AgricultureProceedings of the International Workshop on Big Data in Emergent Distributed Environments10.1145/3663741.3664786(1-6)Online publication date: 9-Jun-2024
  • (2022)Tearing Down the Tower of Babel: Unified and Efficient Spatio-temporal Queries for NoSQL Stores2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00024(19-28)Online publication date: Jun-2022
  • (2021)A demonstration of NoDAProceedings of the VLDB Endowment10.14778/3476311.347636114:12(2851-2854)Online publication date: 28-Oct-2021
  • Show More Cited By

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cover image ACM Other conferences
SSTD '19: Proceedings of the 16th International Symposium on Spatial and Temporal Databases
August 2019
245 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • TU Wien: TU Wien

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2019

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Author Tags

  1. NoSQL
  2. data access operators
  3. spatio-temporal data

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Cited By

View all
  • (2024)Technological and Research Challenges in Data Engineering for Sustainable AgricultureProceedings of the International Workshop on Big Data in Emergent Distributed Environments10.1145/3663741.3664786(1-6)Online publication date: 9-Jun-2024
  • (2022)Tearing Down the Tower of Babel: Unified and Efficient Spatio-temporal Queries for NoSQL Stores2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00024(19-28)Online publication date: Jun-2022
  • (2021)A demonstration of NoDAProceedings of the VLDB Endowment10.14778/3476311.347636114:12(2851-2854)Online publication date: 28-Oct-2021
  • (2021)Towards Unified Modeling for NoSQL Solution Based on Mapping ApproachProcedia Computer Science10.1016/j.procs.2021.09.137192(3637-3646)Online publication date: 2021
  • (2020)The SPADES Framework for Scalable Management of Spatio-textual DataProceedings of the 24th Pan-Hellenic Conference on Informatics10.1145/3437120.3437293(140-143)Online publication date: 20-Nov-2020

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