With the fast growth of the knowledge bases built over the Internet, storing and querying millions or billions of RDF triples in a knowledge base have attracted increasing research interests. Although the latest RDF storage systems achieve good querying performance, few of them pay much attention to the characteristic of dynamic growth of the knowledge base. Since the building of the knowledge base is usually a continuous process, incremental update over the RDF storage system is in great need. In this paper, to consider the efficiency of both querying and incremental update in RDF data, we propose a hAsh-based tWo-tiEr rdf sTOrage system (abbr. to AWETO) with new index architecture and query execution engine. The performance of our system is systematically measured over two large-scale datasets. Compared with the other three state-of-the-art open source RDF storage systems, our system achieves the best incremental update efficiency meanwhile, the query efficiency is competitive.
['Xu Pu', 'Jianyong Wang', 'Zhenhua Song', 'Ping Luo', 'Min Wang']
Editorial: Efficient incremental update and querying in AWETO RDF storage system