2026-09-19T16:40:41Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1134552026-06-06T00:54:42Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael Stonebraker.
Yu, Katherine (Katherine X.)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2018-02-08T15:58:25Z
2018-02-08T15:58:25Z
2017
2017
http://hdl.handle.net/1721.1/113455
1020180216
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 55-56).
The BigDAWG polystore database system aims to address workloads dealing with large, heterogeneous datasets. The need for such a system is motivated by an increase in Big Data applications dealing with disparate types of data, from large scale analytics to realtime data streams to text-based records, each suited for different storage engines. These applications often perform cross-engine queries on correlated data, resulting in complex query planning, data migration, and execution. One such application is a medical application built by the Intel Science and Technology Center (ISTC) on data collected from an intensive care unit (ICU). This thesis presents work done to add support for two commonly used database engines, Vertica and MySQL, to the BigDAWG system, as well as results and analysis from performance evaluation of the system using the TPC-H benchmark.
by Katherine Yu.
M.Eng.
56 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Database engine integration and performance analysis of the BigDAWG polystore system
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>The BigDAWG polystore database system aims to address workloads dealing with large, heterogeneous datasets. The need for such a system is motivated by an increase in Big Data applications dealing with disparate types of data, from large scale analytics to realtime data streams to text-based records, each suited for different storage engines. These applications often perform cross-engine queries on correlated data, resulting in complex query planning, data migration, and execution. One such application is a medical application built by the Intel Science and Technology Center (ISTC) on data collected from an intensive care unit (ICU). This thesis presents work done to add support for two commonly used database engines, Vertica and MySQL, to the BigDAWG system, as well as results and analysis from performance evaluation of the system using the TPC-H benchmark.</Abstract>
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