Authors
Varun Pandey, Andreas Kipf, Dimitri Vorona, Tobias Mühlbauer, Thomas Neumann, Alfons Kemper
Publication date
2016/6/26
Book
Proceedings of the 2016 international conference on management of data
Pages
2145-2148
Description
In the past few years, massive amounts of location-based data has been captured. Numerous datasets containing user location information are readily available to the public. Analyzing such datasets can lead to fascinating insights into the mobility patterns and behaviors of users. Moreover, in recent times a number of geospatial data-driven companies like Uber, Lyft, and Foursquare have emerged. Real-time analysis of geospatial data is essential and enables an emerging class of applications. Database support for geospatial operations is turning into a necessity instead of a distinct feature provided by only a few databases. Even though a lot of database systems provide geospatial support nowadays, queries often do not consider the most current database state. Geospatial queries are inherently slow given the fact that some of these queries require a couple of geometric computations. Disk-based database …
Total citations
2017201820192020202120222023202446385413
Scholar articles
V Pandey, A Kipf, D Vorona, T Mühlbauer, T Neumann… - Proceedings of the 2016 international conference on …, 2016