The BigDAWG Polystore System and Architecture
© 2016 IEEE. Organizations are often faced with the challenge of providing data management solutions for large, heterogenous datasets that may have different underlying data and programming models. For example, a medical dataset may have unstructured text, relational data, time series waveforms and...
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2021
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| Online Access: | https://hdl.handle.net/1721.1/137777 |
| _version_ | 1826215223667720192 |
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| author | Gadepally, Vijay Chen, Peinan Duggan, Jennie Elmore, Aaron Haynes, Brandon Kepner, Jeremy Madden, Samuel Mattson, Tim Stonebraker, Michael |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Gadepally, Vijay Chen, Peinan Duggan, Jennie Elmore, Aaron Haynes, Brandon Kepner, Jeremy Madden, Samuel Mattson, Tim Stonebraker, Michael |
| author_sort | Gadepally, Vijay |
| collection | MIT |
| description | © 2016 IEEE. Organizations are often faced with the challenge of providing data management solutions for large, heterogenous datasets that may have different underlying data and programming models. For example, a medical dataset may have unstructured text, relational data, time series waveforms and imagery. Trying to fit such datasets in a single data management system can have adverse performance and efficiency effects. As a part of the Intel Science and Technology Center on Big Data, we are developing a polystore system designed for such problems. BigDAWG (short for the Big Data Analytics Working Group) is a polystore system designed to work on complex problems that naturally span across different processing or storage engines. BigDAWG provides an architecture that supports diverse database systems working with different data models, support for the competing notions of location transparency and semantic completeness via islands and a middleware that provides a uniform multi-island interface. Initial results from a prototype of the BigDAWG system applied to a medical dataset validate polystore concepts. In this article, we will describe polystore databases, the current BigDAWG architecture and its application on the MIMIC II medical dataset, initial performance results and our future development plans. |
| first_indexed | 2024-09-23T16:19:23Z |
| format | Article |
| id | mit-1721.1/137777 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:19:23Z |
| publishDate | 2021 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1377772022-09-29T19:34:45Z The BigDAWG Polystore System and Architecture Gadepally, Vijay Chen, Peinan Duggan, Jennie Elmore, Aaron Haynes, Brandon Kepner, Jeremy Madden, Samuel Mattson, Tim Stonebraker, Michael Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Lincoln Laboratory © 2016 IEEE. Organizations are often faced with the challenge of providing data management solutions for large, heterogenous datasets that may have different underlying data and programming models. For example, a medical dataset may have unstructured text, relational data, time series waveforms and imagery. Trying to fit such datasets in a single data management system can have adverse performance and efficiency effects. As a part of the Intel Science and Technology Center on Big Data, we are developing a polystore system designed for such problems. BigDAWG (short for the Big Data Analytics Working Group) is a polystore system designed to work on complex problems that naturally span across different processing or storage engines. BigDAWG provides an architecture that supports diverse database systems working with different data models, support for the competing notions of location transparency and semantic completeness via islands and a middleware that provides a uniform multi-island interface. Initial results from a prototype of the BigDAWG system applied to a medical dataset validate polystore concepts. In this article, we will describe polystore databases, the current BigDAWG architecture and its application on the MIMIC II medical dataset, initial performance results and our future development plans. 2021-11-08T18:55:12Z 2021-11-08T18:55:12Z 2016-09 2019-06-18T13:40:45Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137777 Gadepally, Vijay, Chen, Peinan, Duggan, Jennie, Elmore, Aaron, Haynes, Brandon et al. 2016. "The BigDAWG Polystore System and Architecture." en 10.1109/hpec.2016.7761636 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv |
| spellingShingle | Gadepally, Vijay Chen, Peinan Duggan, Jennie Elmore, Aaron Haynes, Brandon Kepner, Jeremy Madden, Samuel Mattson, Tim Stonebraker, Michael The BigDAWG Polystore System and Architecture |
| title | The BigDAWG Polystore System and Architecture |
| title_full | The BigDAWG Polystore System and Architecture |
| title_fullStr | The BigDAWG Polystore System and Architecture |
| title_full_unstemmed | The BigDAWG Polystore System and Architecture |
| title_short | The BigDAWG Polystore System and Architecture |
| title_sort | bigdawg polystore system and architecture |
| url | https://hdl.handle.net/1721.1/137777 |
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