Modelagem de banco de dados não relacional em Plataforma Big Data visando dados de internet das coisas

Abstract

Internet of Things works with a great amount of devices connected to Internet and the constant growth of users who use these devices, generates a huge mass of data that grows every year, for this reason Big Data has been the most recommended to store the generated data. This work aimed to help in this need to improve the storage of the data and to make it available more quickly through a non-relational database modeling based on Big Data. Data export tests were performed in PostgreSQL relational database and imported this data into a non-relational database MongoDB from two different meteorological data sources. These tests verified the flexibility and scalability of the modeling. Was also performs tests that verified the performance of the database with this modeling through queries performed directly in the MongoDB database. Tests that also found a difficulty in the query with more than 50 thousand records executed in the graphical interface Robomongo. Difficulty is this that doesn’t prevent the use of modeling for its main purpose that is storage, flexible, adaptable and scalable.