Model 204 Architecture and Performance
Proceedings of the 2nd International Workshop on High Performance Transaction Systems
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Scalable semantic web data management using vertical partitioning
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
YAGO: A Large Ontology from Wikipedia and WordNet
Web Semantics: Science, Services and Agents on the World Wide Web
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
LUBM: A benchmark for OWL knowledge base systems
Web Semantics: Science, Services and Agents on the World Wide Web
Matrix "Bit" loaded: a scalable lightweight join query processor for RDF data
Proceedings of the 19th international conference on World wide web
Efficient RDF data management including provenance and uncertainty
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
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The Resource Description Framework (RDF) is a popular data model for representing linked data sets arising from the web, as well as large scientific data repositories such as UniProt. RDF data intrinsically represents a labeled and directed multi-graph. SPARQL is a query language for RDF that expresses subgraph pattern-finding queries on this implicit multigraph in a SQL-like syntax. SPARQL queries generate complex intermediate join queries; to compute these joins efficiently, this paper presents a new strategy based on bitmap indexes. We store the RDF data in column-oriented compressed bitmap structures, along with two dictionaries. We find that our bitmap index-based query evaluation approach is up to an order of magnitude faster the state-of-the-art system RDF-3X, for a variety of SPARQL queries on gigascale RDF data sets.