Análisis de bases de datos relacionales y no relacionales aplicado al problema de la ruta más corta.
years ago, SQL technology was the primary data modeling and processing tool. Still, in actuality, it leaves many fallancies and does not provide the necessary capabilities to work with massive data. The present research compares the shortest path route's calculation using the dijkstra algorithm...
Gorde:
| Egile nagusia: | |
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| Beste egile batzuk: | |
| Formatua: | bachelorThesis |
| Hizkuntza: | spa |
| Argitaratua: |
2021
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| Gaiak: | |
| Sarrera elektronikoa: | http://dspace.unach.edu.ec/handle/51000/7540 |
| Etiketak: |
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Etiketa erantsi | Gaia: | years ago, SQL technology was the primary data modeling and processing tool. Still, in actuality, it leaves many fallancies and does not provide the necessary capabilities to work with massive data. The present research compares the shortest path route's calculation using the dijkstra algorithm in postgresql with the pgrouting extension used for network analysis and route planning. In contrast, neo4j uses the declarative language inspired SQL by cypher, which has the dijkstra algorithm at its core. The comparison was made using the road networks of the city of quito, obtained from openstreetmap. Neo4j does not support the native openstreetmap format (.Osm), so the additional tool osmnx is used, a python package manager, to download road networks in the city of quito in a (.Graphml) format acceptable to its neo4j manager. The results obtained in this study show a performance superiority in the response times of calculating the shortest path route in favor neo4j. Despite not being a database-oriented to road networks' routine, it develops with very noticeable and efficient agility. Neo4j has improved its support in geospatial data processing in its latest versions, making it a powerful solution alternative to conventional managers. |
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