Resumen de Study Case: The Database Selection Process for the Big Data-based System to Reduce Health Effects of Air Pollution in Ciudad Juárez, Mexico
Adrián Vázquez, Fernando Estrada Saldaña, Alicia Jiménez, Angel Nieves, Nabile Rodríguez, Israel Hernández
The Border 2020 is a U.S.-Mexico effort to address binational environmental problems along the border. This project involved the city of El Paso, Texas and Ciudad Juárez, México to improve the transboundary air quality. A large portion of the Ciudad Juarez population resides in areas with very few or none air quality monitoring stations and also people is not educated on the health effects of exposure to air pollution. This motivated an innovative community-based climate monitoring scheme to increase the awareness among people on the effects of air pollutions. The idea was to manufacture a large amount of low-cost air quality sensors, located at different strategic sites to cover a major portion of the city and then to measure and analyze meteorological variables and alert people about outdoor activities when their health is at risk. To achieve this, it was considered a big data-based system to collect, store, analyze and visualize a large amount of data. Selecting the appropriate database software to store large volumes of data is a key element in these projects. Recent advances in storage technology show two main approaches of databases: SQL relational and NoSQL non-relational databases. This paper discusses important factors to consider when selecting the database software for climate data and presents a performance comparison between SQL and NoSQL databases in specific scenarios involving operations such as inserting, deleting and updating a massive volume of both structured and unstructured data
