demonstration

TyphonML: a modeling environment to develop hybrid polystores

Authors:

Ludovico IovinoAuthors Info & Claims

MODELS '20: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings

Article No.: 2, Pages 1 - 5

https://doi.org/10.1145/3417990.3421999

Published: 26 October 2020 Publication History

Get Access

Abstract

Designing and deploying a hybrid data persistence architecture that involves a combination of relational and NoSQL databases is a complex, technically challenging, and error-prone task. In this tool paper, we propose TyphonML, a modeling language and supporting environment, which permits modelers to specify data that need to be persisted in hybrid architectures, by abstracting over the specificities of the underlying technologies. The language enables the specification of both conceptual entities and available data layer technologies, and then how the modeled entities have to be mapped to the available database systems. TyphonML models are used to generate microservice-based infrastructures, which permit users to interact with the designed hybrid polystores at the conceptual level. In this tool paper, we show the different components of the TyphonML environment at work through a demonstration scenario.

References

[1]

Paolo Atzeni, Francesca Bugiotti, and Luca Rossi. 2014. Uniform access to NoSQL systems. Information Systems 43 (2014), 117 -- 133.

Digital Library

Google Scholar

[2]

F. Budinsky, D. Steinberg, E. Merks, R. Ellersick, and T.J. Grose. 2003. Eclipse Modeling Framework. Addison Wesley.

Google Scholar

[3]

Subhasis Dasgupta, Kevin Coakley, and Amarnath Gupta. 2016. Analytics-driven data ingestion and derivation in the AWESOME polystore. In 2016 IEEE International Conference on Big Data (Big Data). 2555--2564.

Crossref

Google Scholar

[4]

Jennie Duggan, Aaron J. Elmore, Michael Stonebraker, Magda Balazinska, Bill Howe, Jeremy Kepner, Sam Madden, David Maier, Tim Mattson, and Stan Zdonik. 2015. The BigDAWG Polystore System. ACM SIGMOD Record 44, 2 (Aug. 2015), 11--16.

Digital Library

Google Scholar

[5]

Mohammed El Mohajir and Amal Latrache. 2012. Unifying and incorporating functional and non functional requirements in datawarehouse conceptual design. In 2012 Colloquium in Information Science and Technology. 49--57. ISSN: 2327-1884.

Crossref

Google Scholar

[6]

Luc Engelen and Mark van den Brand. 2010. Integrating textual and graphical modelling languages. Electronic Notes in Theoretical Computer Science 253, 7 (2010), 105--120.

Digital Library

Google Scholar

[7]

Vijay Gadepally, Peinan Chen, Jennie Duggan, Aaron Elmore, Brandon Haynes, Jeremy Kepner, Samuel Madden, Tim Mattson, and Michael Stonebraker. 2016. The BigDAWG polystore system and architecture. In 2016 IEEE High Performance Extreme Computing Conference (HPEC). 1--6.

Crossref

Google Scholar

[8]

Felix Gessert, Florian Bücklers, and Norbert Ritter. 2014. Orestes: A scalable Database-as-a-Service architecture for low latency. In 2014 IEEE 30th International Conference on Data Engineering Workshops. 215--222. ISSN: null.

Crossref

Google Scholar

[9]

Dimitrios S Kolovos, Richard F Paige, and Fiona AC Polack. 2006. The epsilon object language (EOL). In European Conference on Model Driven Architecture-Foundations and Applications. Springer, 128--142.

Digital Library

Google Scholar

[10]

Jiaheng Lu, Irena Holubová, and Bogdan Cautis. 2018. Multi-model databases and tightly integrated polystores: Current practices, comparisons, and open challenges. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2301--2302.

Digital Library

Google Scholar

[11]

Sam Newman. 2015. Building microservices: designing fine-grained systems. "O'Reilly Media, Inc.".

Google Scholar

[12]

Fá Rilston Silva Paim and Jaelson Castro. 2002. Enhancing Data Warehouse Design with the NFR Framework. In Anais do WER02 - Workshop em Engenharia de Requisitos, Valencia, España, Novembro 11-12, 2002, Oscar Pastor and Juan Sánchez Díaz (Eds.). 40--57. http://wer.inf.puc-rio.br/WERpapers/artigos/artigos_WER02/paim.pdf

Google Scholar

[13]

Tushar Sharma, Marios Fragkoulis, Stamatia Rizou, Magiel Bruntink, and Diomidis Spinellis. 2018. Smelly relations: measuring and understanding database schema quality. In Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Practice. ACM, 55--64.

Digital Library

Google Scholar

[14]

Vasilis Spyropoulos, Christina Vasilakopoulou, and Yannis Kotidis. 2016. Digree: A middleware for a graph databases polystore. In 2016 IEEE International Conference on Big Data (Big Data). 2580--2589.

Crossref

Google Scholar

Cited By

View all

Asaad C(2023)Towards Leveraging Artificial Intelligence for NoSQL Data Modeling, Querying and Quality Characterization2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C59198.2023.00047(192-198)Online publication date: 1-Oct-2023
https://doi.org/10.1109/MODELS-C59198.2023.00047
Basciani FDi Rocco JIovino LPierantonio A(2023)TyphonML: Tool Support for Hybrid PolystoresScience of Computer Programming10.1016/j.scico.2023.103044(103044)Online publication date: Oct-2023
https://doi.org/10.1016/j.scico.2023.103044
Gobert MMeurice LCleve A(2023)Modeling, Manipulating and Evolving Hybrid Polystores with HyDRaScience of Computer Programming10.1016/j.scico.2023.102972(102972)Online publication date: May-2023
https://doi.org/10.1016/j.scico.2023.102972
Show More Cited By

Index Terms

TyphonML: a modeling environment to develop hybrid polystores
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software system models
        Model-driven software engineering

Recommendations

Database technologies in the world of big data
CompSysTech '15: Proceedings of the 16th International Conference on Computer Systems and Technologies

Now we have a number of database technologies called usually NoSQL, like key-value, column-oriented, and document stores as well as search engines and graph databases. Whereas SQL software vendors offer advanced products with the capability to handle ...
UML and model-driven development for SoC design
CODES+ISSS '06: Proceedings of the 4th international conference on Hardware/software codesign and system synthesis

UML (Unified Modeling Language™) as an OMG standard has received wide acceptance in software engineering over the last years. As electronic systems design moved towards software engineering, there is emerging interest for UML within the hardware ...
Tool support for teaching responsibility-driven design
ITiCSE '09

We present Trace Modeler, a specialized tool that helps students understand and apply responsibility-driven design.

Comments

Information & Contributors

Information

Published In

MODELS '20: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings

October 2020

713 pages

ISBN:9781450381352

DOI:10.1145/3417990

Conference Chairs:
Esther Guerra
Universidad Autonoma de Madrid, Spain
,
Ludovico Iovino
Gran Sasso Science Institute, Italy

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

In-Cooperation

IEEE CS

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2020

Check for updates

Author Tags

Qualifiers

Demonstration

Conference

MODELS '20

Sponsor:

SIGSOFT

MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems

October 16 - 23, 2020

Virtual Event, Canada

Acceptance Rates

Overall Acceptance Rate 118 of 382 submissions, 31%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
149
Total Downloads

Downloads (Last 12 months)19
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Asaad C(2023)Towards Leveraging Artificial Intelligence for NoSQL Data Modeling, Querying and Quality Characterization2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C59198.2023.00047(192-198)Online publication date: 1-Oct-2023
https://doi.org/10.1109/MODELS-C59198.2023.00047
Basciani FDi Rocco JIovino LPierantonio A(2023)TyphonML: Tool Support for Hybrid PolystoresScience of Computer Programming10.1016/j.scico.2023.103044(103044)Online publication date: Oct-2023
https://doi.org/10.1016/j.scico.2023.103044
Gobert MMeurice LCleve A(2023)Modeling, Manipulating and Evolving Hybrid Polystores with HyDRaScience of Computer Programming10.1016/j.scico.2023.102972(102972)Online publication date: May-2023
https://doi.org/10.1016/j.scico.2023.102972
Koupil PHolubová I(2022)A unified representation and transformation of multi-model data using category theoryJournal of Big Data10.1186/s40537-022-00613-39:1Online publication date: 3-May-2022
https://doi.org/10.1186/s40537-022-00613-3
Conrad AUtzmann PKlettke MStörl UKühn TSousa V(2022)Metamodels to support database migration between heterogeneous data storesProceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings10.1145/3550356.3561574(546-551)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3550356.3561574
Koupil PHolubová IHong JBures MPark JCerny T(2022)Unifying categorical representation of multi-model dataProceedings of the 37th ACM/SIGAPP Symposium on Applied Computing10.1145/3477314.3507690(365-371)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3477314.3507690
Koupil PSvoboda MHolubova I(2021)MM-cat: A Tool for Modeling and Transformation of Multi-Model Data using Category Theory2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)10.1109/MODELS-C53483.2021.00098(635-639)Online publication date: Oct-2021
https://doi.org/10.1109/MODELS-C53483.2021.00098
Benats PGobert MMeurice LNagy CCleve A(2021)An Empirical Study of (Multi-) Database Models in Open-Source ProjectsConceptual Modeling10.1007/978-3-030-89022-3_8(87-101)Online publication date: 16-Oct-2021
https://doi.org/10.1007/978-3-030-89022-3_8
Gobert MMeurice LCleve A(2021)Conceptual Modeling of Hybrid PolystoresConceptual Modeling10.1007/978-3-030-89022-3_10(113-122)Online publication date: 16-Oct-2021
https://doi.org/10.1007/978-3-030-89022-3_10
Svoboda MČontoš PHolubová I(2021)Categorical Modeling of Multi-model Data: One Model to Rule Them AllModel and Data Engineering10.1007/978-3-030-78428-7_15(190-198)Online publication date: 14-Jun-2021
https://doi.org/10.1007/978-3-030-78428-7_15
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Database technologies in the world of big data

UML and model-driven development for SoC design

Tool support for teaching responsibility-driven design

Comments

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Upcoming Conference

Other Metrics

Article Metrics

Other Metrics

Cited By

Login options

Full Access

PDF

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Database technologies in the world of big data

UML and model-driven development for SoC design

Tool support for teaching responsibility-driven design

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Upcoming Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Get Access

Login options

Full Access

View options

PDF

eReader

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations