TY - JOUR
T1 - How good are modern spatial analytics systems?
AU - Pandey, Varun
AU - Kipf, Andreas
AU - Neumann, Thomas
AU - Kemper, Alfons
N1 - Publisher Copyright:
© 2018 VLDB Endowment.
PY - 2018
Y1 - 2018
N2 - Spatial data is pervasive. Large amount of spatial data is produced every day from GPS-enabled devices such as cell phones, cars, sensors, and various consumer based applications such as Uber, location-tagged posts in Facebook, Instagram, Snapchat, etc. This growth in spatial data coupled with the fact that spatial queries, analytical or transactional, can be computationally extensive has attracted enormous interest from the research community to develop systems that can efficiently process and analyze this data. In recent years a lot of spatial analytics systems have emerged. Existing work compares either limited features of these systems or the studies are outdated since new systems have emerged. In this work, we first explore the available modern spatial processing systems and then thoroughly compare them based on features and queries they support, using real-world datasets.
AB - Spatial data is pervasive. Large amount of spatial data is produced every day from GPS-enabled devices such as cell phones, cars, sensors, and various consumer based applications such as Uber, location-tagged posts in Facebook, Instagram, Snapchat, etc. This growth in spatial data coupled with the fact that spatial queries, analytical or transactional, can be computationally extensive has attracted enormous interest from the research community to develop systems that can efficiently process and analyze this data. In recent years a lot of spatial analytics systems have emerged. Existing work compares either limited features of these systems or the studies are outdated since new systems have emerged. In this work, we first explore the available modern spatial processing systems and then thoroughly compare them based on features and queries they support, using real-world datasets.
UR - http://www.scopus.com/inward/record.url?scp=85058890320&partnerID=8YFLogxK
U2 - 10.14778/3236187.3236213
DO - 10.14778/3236187.3236213
M3 - Conference article
AN - SCOPUS:85058890320
SN - 2150-8097
VL - 11
SP - 1661
EP - 1673
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 11
T2 - 44th International Conference on Very Large Data Bases, VLDB 2018
Y2 - 27 August 2018 through 31 August 2018
ER -