Loading [a11y]/accessibility-menu.js
Jackpine: A benchmark to evaluate spatial database performance | IEEE Conference Publication | IEEE Xplore

Jackpine: A benchmark to evaluate spatial database performance


Abstract:

The volume of spatial data generated and consumed is rising exponentially and new applications are emerging as the costs of storage, processing power and network bandwidt...Show More

Abstract:

The volume of spatial data generated and consumed is rising exponentially and new applications are emerging as the costs of storage, processing power and network bandwidth continue to decline. Database support for spatial operations is fast becoming a necessity rather than a niche feature provided by a few products. However, the spatial functionality offered by current commercial and open-source relational databases differs significantly in terms of available features, true geodetic support, spatial functions and indexing. Benchmarks play a crucial role in evaluating the functionality and performance of a particular database, both for application users and developers, and for the database developers themselves. In contrast to transaction processing, however, there is no standard, widely used benchmark for spatial database operations. In this paper, we present a spatial database benchmark called Jackpine. Our benchmark is portable (it can support any database with a JDBC driver implementation) and includes both micro benchmarks and macro workload scenarios. The micro benchmark component tests basic spatial operations in isolation; it consists of queries based on the Dimensionally Extended 9-intersection model of topological relations and queries based on spatial analysis functions. Each macro workload includes a series of queries that are based on a common spatial data application. These macro scenarios include map search and browsing, geocoding, reverse geocoding, flood risk analysis, land information management and toxic spill analysis. We use Jackpine to evaluate the spatial features in 2 open source databases and 1 commercial offering.
Date of Conference: 11-16 April 2011
Date Added to IEEE Xplore: 16 May 2011
ISBN Information:

ISSN Information:

Conference Location: Hannover, Germany

I. Introduction

Spatial data is everywhere. Geospatial Web services such as Google Maps, in-vehicle GPS navigation systems, GPS-enabled mobile phones, and a host of accompanying location-based services have become part of our daily experience. Enormous quantities of spatial data is constantly being generated from various sources such as satellites, sensors and mobile devices. NASA's Earth Observing System (EOS), for instance, generates 1 terabyte of data every day [1]. A decade ago, it was estimated that 80% of all business data stored in existing databases had spatial attributes [2]. The percentage today is probably even higher, as the ability to track customers and inventory has become cheaper and easier.

Contact IEEE to Subscribe

References

References is not available for this document.