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QUEPA: QUerying and Exploring a Polystore by Augmentation

Published: 26 June 2016 Publication History

Abstract

Polystore systems (or simply polystores) have been recently proposed to support a common scenario in which enterprise data are stored in a variety of database technologies relying on different data models and languages. Polystores provide a loosely coupled integration of data sources and support the direct access, with the local language, to each specific storage engine to exploit its distinctive features. Given the absence of a global schema, new challenges for accessing data arise in these environments. In fact, it is usually hard to know in advance if a query to a specific data store can be satisfied with data stored elsewhere in the polystore. QUEPA addresses these issues by introducing augmented search and augmented exploration in a polystore, two access methods based on the automatic enrichment of the result of a query over a storage system with related data in the rest of the polystore. These features do not impact on the applications running on top of the polystore and are compatible with the most common database systems. QUEPA implements in this way a lightweight mechanism for data integration in the polystore and operates in a plug-and-play mode, thus reducing the need for ad-hoc configurations and for middleware layers involving standard APIs, unified query languages or shared data models. In our demonstration audience can experience with the augmentation construct by using the native query languages of the database systems available in the polystore.

References

[1]
Apache MetaModel. http://metamodel.apache.org/, (accessed January, 2016).
[2]
UnQL: Unstructured Data Query Language. http://www.couchbase.com/press-releases/unql-query-language, (accessed January, 2016).
[3]
P. Atzeni, F. Bugiotti, and L. Rossi. Uniform access to nosql systems. Inf. Syst., 43:117--133, 2014.
[4]
M. Buoncristiano et al. Database challenges for exploratory computing. SIGMOD Record, 44(2):17--22, 2015.
[5]
J. Duggan et al. The BigDAWG polystore system. SIGMOD Record, 44(2):11--16, 2015.
[6]
K. Morton, M. Balazinska, D. Grossman, and J. D. Mackinlay. Support the data enthusiast: Challenges for next-generation data-analysis systems. PVLDB, 7(6):453--456, 2014.
[7]
R. Pottinger and P. A. Bernstein. Schema merging and mapping creation for relational sources. In EDBT, pages 73--84, 2008.
[8]
M. Stonebraker. The case for polystores. http://wp.sigmod.org/?p=1629, July, 2015.

Cited By

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  • (2023)Empowering Data Federation Security in Polystore Systems2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA59173.2023.10479321(1-8)Online publication date: 4-Dec-2023
  • (2023)TyphonML: Tool Support for Hybrid PolystoresScience of Computer Programming10.1016/j.scico.2023.103044(103044)Online publication date: Oct-2023
  • (2022)Polyglot data managementProceedings of the VLDB Endowment10.14778/3554821.355489115:12(3750-3753)Online publication date: 1-Aug-2022
  • Show More Cited By

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cover image ACM Conferences
SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data
June 2016
2300 pages
ISBN:9781450335317
DOI:10.1145/2882903
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 the author(s) 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2016

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Author Tags

  1. BYOL
  2. augmentation
  3. augmented exploration
  4. augmented search
  5. explorative querying
  6. noSQL
  7. polyglot persistence
  8. polystore

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  • Research-article

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SIGMOD/PODS'16
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SIGMOD/PODS'16: International Conference on Management of Data
June 26 - July 1, 2016
California, San Francisco, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all
  • (2023)Empowering Data Federation Security in Polystore Systems2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)10.1109/AICCSA59173.2023.10479321(1-8)Online publication date: 4-Dec-2023
  • (2023)TyphonML: Tool Support for Hybrid PolystoresScience of Computer Programming10.1016/j.scico.2023.103044(103044)Online publication date: Oct-2023
  • (2022)Polyglot data managementProceedings of the VLDB Endowment10.14778/3554821.355489115:12(3750-3753)Online publication date: 1-Aug-2022
  • (2018)Augmented Access for Querying and Exploring a Polystore2018 IEEE 34th International Conference on Data Engineering (ICDE)10.1109/ICDE.2018.00017(77-88)Online publication date: Apr-2018
  • (2018)Polypheny-DB: Towards a Distributed and Self-Adaptive Polystore2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8622353(3364-3373)Online publication date: Dec-2018
  • (2017)BigDAWG version 0.12017 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC.2017.8091077(1-7)Online publication date: Sep-2017
  • (2017)Integrated access to big data polystores through a knowledge-driven framework2017 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2017.8258083(1494-1503)Online publication date: Dec-2017
  • (2016)MuSQLE: Distributed SQL query execution over multiple engine environments2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840636(452-461)Online publication date: Dec-2016
  • (2016)Mix ‘n’ match multi-engine analytics2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840605(194-203)Online publication date: Dec-2016

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