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.
En la actualidad, se genera gran cantidad de información y datos, es por esto que aparecen soluciones alternativas a lo ya existente, tal es el caso de las bases de datos no relacionales o NoSQL, dichas bases de datos funcionan mejor ante un gran volumen de datos en comparación con las SQL. Sin embargo, se han publicado varias investigaciones en cuanto al rendimiento de las bases de datos NoSQL, pero no existe mucha información acerca del comportamiento que tienen estos Sistemas Gestores de Bases de Datos (SGBD) con datos geográficos, es por esto que el presente artículo plantea una comparación en cuanto al tiempo de respuesta entre los SGBD MongoDB y ArangoDB. Para realizar esta comparación se realizaron pruebas en dos escenarios de prueba, denominados 100% lectura y 95% lectura–5% escritura. Además, para ambos escenarios se ejecutaron 10 diferentes tamaños de operación. Los resultados obtenidos permiten concluir que, en ambos escenarios estudiados, el SGBD que presentó un mejor desempeño fue el de MongoDB.
Planning for the transformation of a destination into a smart tourist destination must consider the use of state-of-the-art technology as an essential requirement. This article describes how to use technology to drive the process of transforming Costa Rica's La Fortuna destination into a smart tourist destination. The methodology was assumed through a multimethod design in which a case study was developed in La Fortuna destination in collaboration with the Arenal Cámara de Turismo y Comercio. Therefore, it was possible to determine and characterize the technologies used in the main smart tourist destinations, the SWOT analysis factor of La Fortuna tourist destination with the greatest applicability of technologies and the design of an information system for La Fortuna. These results can be used as a reference point by other tourist destinations with similar characteristics to La Fortuna and that wish to start the process of transformation into a smart tourist destination.
<p>Las Infraestructuras de Datos Espaciales (IDE) permiten primordialmente la administración y publicación de información geográfica ya sea de índole nacional, regional o local, logrando con esto el potencial establecimiento de una red de nodos de diversos actores proveedores de datos que permita la interrelación de información. En este contexto, la IDE Huetar Norte de Costa Rica (IDEHN) se creó con el propósito de proveer información regional de diversas fuentes.</p><p>Para la consulta de esta información, la IDEHN facilita el uso de geoservicios que permiten el acceso remoto de los datos a través de geoportales, herramientas para Sistemas de Información Geográficos e inclusive a través de aplicaciones de software a la medida para escritorio o dispositivos móviles.</p><p>En relación con este espacio de trabajo de desarrollo de aplicaciones a la medida, este artículo presenta tres casos de éxito en el uso de geoservicios proporcionados por la IDEHN para gestionar información geográfica en dispositivos móviles.</p>
Web mapping services provide information directly to users and other software programs that can consume and produce information. One of the main challenges this type of service presents is improving its performance. Therefore, in this research, a new geoservice integrated into GeoServer was developed, called GeoToroTur, with an OWS implementation of vector layers that consumes the information from a hybrid and distributed database that was implemented with PostgreSQL and MongoDB, making use of ToroDB for document replication. This geoservice was evaluated by executing geographic and descriptive attribute filter queries. Based on the results, we can conclude that the response time for GeoToroTur is shorter than that for Geoserver.
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