ĭistributed database systems have been proven instrumental in the effort to dealing with this data deluge.
At the same time, numerous business applications are emerging by processing the 285 billion points regarding aircraft movements per year gathered from the Automatic Dependent Surveillance Broadcast (ADS-B) system and the 60Mb of AIS and weather data collected every second by MarineTraffic’s on-line monitoring service or the 4 millions geotagged tweets daily produced at Twitter. For example, mysteries are unravelled by harnessing the 1 TB of data that is generated per day from NASA’s Earth Observing System, or the more than 140 GB of raw science spatial data every week generated by space Hubble telescope. Managing and analyzing these data is becoming increasingly important, enabling novel applications that may transform science and society. The volumes of spatial data that modern-day systems are generating has met staggering growth during the last few years. Furthermore, the average response time is radically reduced with the use of indexes, especially in the case of MongoDB. The evaluation is based upon real, business scenarios and their subsequent queries as well as their underlying infrastructures and concludes in confirming the superiority of PostgreSQL in almost all cases with the exception of the polygon intersection queries. In particular, the work conducted, set to identify the most efficient data store system in terms of response times, comparing two of the most representative of the two categories (NoSQL and relational), i.e. This work is motivated by the question of which of those data storage systems is better suited to address the needs of industrial applications. The most prominent case is perhaps the data storage systems, that have developed a large number of functionalities to efficiently support spatio-temporal data operations. As such, in order to meet the application requirements, more and more systems are adapting to the specificities of those data. Several modern day problems need to deal with large amounts of spatio-temporal data.
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