A High-Performance Spatial Storage System Based on Main-Memory Database Architecture

Abstract

Newly emerging spatial applications such as the intelligent transportation system require high-performance access to databases. Although research prototypes and spatial extensions on top of commercial DBMSs have been built, the high-performance requirement is difficult to satisfy because most of them employ the traditional disk-based database architecture. With the steadily increasing memory capacity of computer systems, the main-memory database architecture becomes a feasible approach to meeting the requirement, and a few commercial products are developed recently. However, there has been little work on applying the main-memory database to the spatial domain. This paper presents Xmas-SX, a high-performance spatial storage system based on the main-memory database architecture. It provides the core subset of the OpenGIS geometry types, operators, and spatial indexes. Variable-length spatial data are efficiently managed by storing each of them as a sequence of fixed-size fragments. An experiment shows that, compared with a disk-based ODBMS with data fully cached, Xmas-SX shows only 6% better performance for the spatial range query. Before data fully cached, however, the performance gap is much bigger. For the update, Xmas-SX outperforms the ODBMS by more than ten times.