Hybrid storage engine for geospatial data using NoSQL and SQL paradigms
The design and implementation of services to handle geospatial data involves thinking about storage engine performance and optimization for the desired use. NoSQL and relational databases bring their own advantages; therefore, it is necessary to choose one of these options according to the requireme...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Spanish |
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Instituto Tecnológico de Costa Rica
2021-02-01
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| Series: | Tecnología en Marcha |
| Subjects: | |
| Online Access: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4822 |
| _version_ | 1811317587506626560 |
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| author | José A. Herrera-Ramírez Marlen Treviño-Villalobos Leonardo Víquez-Acuña |
| author_facet | José A. Herrera-Ramírez Marlen Treviño-Villalobos Leonardo Víquez-Acuña |
| author_sort | José A. Herrera-Ramírez |
| collection | DOAJ |
| description | The design and implementation of services to handle geospatial data involves thinking about storage engine performance and optimization for the desired use. NoSQL and relational databases bring their own advantages; therefore, it is necessary to choose one of these options according to the requirements of the solution. These requirements can change, or some operations may be performed in a more efficient way on another database engine, so using just one engine means being tied to its features and work model. This paper presents a hybrid approach (NoSQL-SQL) to store geospatial data on MongoDB, which are replicated and mapped on a PostgreSQL database, using an open source tool called ToroDB Stampede; solutions then can take advantage from either NoSQL or SQL features, to satisfy most of the requirements associated to the storage engine performance. A descriptive analysis to explain the workflow of the replication and synchronization in both engines precedes the quantitative analysis by which it was possible to determine that a normal database in PostgreSQL has a shorter response time than to perform the query in PostgreSQL with the hybrid database. In addition, the type of geometry increases the update response time of a materialized view. |
| first_indexed | 2024-04-13T12:10:55Z |
| format | Article |
| id | doaj.art-975bfa6468ad42359006d60c1c29c136 |
| institution | Directory Open Access Journal |
| issn | 0379-3982 2215-3241 |
| language | Spanish |
| last_indexed | 2024-04-13T12:10:55Z |
| publishDate | 2021-02-01 |
| publisher | Instituto Tecnológico de Costa Rica |
| record_format | Article |
| series | Tecnología en Marcha |
| spelling | doaj.art-975bfa6468ad42359006d60c1c29c1362022-12-22T02:47:29ZspaInstituto Tecnológico de Costa RicaTecnología en Marcha0379-39822215-32412021-02-01ág. 405410.18845/tm.v34i1.48224124Hybrid storage engine for geospatial data using NoSQL and SQL paradigmsJosé A. Herrera-Ramírez0Marlen Treviño-Villalobos1https://orcid.org/0000-0002-1135-0650Leonardo Víquez-Acuña2Instituto Tecnológico de Costa RicaInstituto Tecnológico de Costa RicaInstituto Tecnológico de Costa RicaThe design and implementation of services to handle geospatial data involves thinking about storage engine performance and optimization for the desired use. NoSQL and relational databases bring their own advantages; therefore, it is necessary to choose one of these options according to the requirements of the solution. These requirements can change, or some operations may be performed in a more efficient way on another database engine, so using just one engine means being tied to its features and work model. This paper presents a hybrid approach (NoSQL-SQL) to store geospatial data on MongoDB, which are replicated and mapped on a PostgreSQL database, using an open source tool called ToroDB Stampede; solutions then can take advantage from either NoSQL or SQL features, to satisfy most of the requirements associated to the storage engine performance. A descriptive analysis to explain the workflow of the replication and synchronization in both engines precedes the quantitative analysis by which it was possible to determine that a normal database in PostgreSQL has a shorter response time than to perform the query in PostgreSQL with the hybrid database. In addition, the type of geometry increases the update response time of a materialized view.https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4822databasesqlnosqltorodbmongodbpostgresqlreplicationmirroring |
| spellingShingle | José A. Herrera-Ramírez Marlen Treviño-Villalobos Leonardo Víquez-Acuña Hybrid storage engine for geospatial data using NoSQL and SQL paradigms Tecnología en Marcha database sql nosql torodb mongodb postgresql replication mirroring |
| title | Hybrid storage engine for geospatial data using NoSQL and SQL paradigms |
| title_full | Hybrid storage engine for geospatial data using NoSQL and SQL paradigms |
| title_fullStr | Hybrid storage engine for geospatial data using NoSQL and SQL paradigms |
| title_full_unstemmed | Hybrid storage engine for geospatial data using NoSQL and SQL paradigms |
| title_short | Hybrid storage engine for geospatial data using NoSQL and SQL paradigms |
| title_sort | hybrid storage engine for geospatial data using nosql and sql paradigms |
| topic | database sql nosql torodb mongodb postgresql replication mirroring |
| url | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4822 |
| work_keys_str_mv | AT joseaherreraramirez hybridstorageengineforgeospatialdatausingnosqlandsqlparadigms AT marlentrevinovillalobos hybridstorageengineforgeospatialdatausingnosqlandsqlparadigms AT leonardoviquezacuna hybridstorageengineforgeospatialdatausingnosqlandsqlparadigms |