Graph-theoretic methods in database theory
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A methodology for database system performance evaluation
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Transitive Closure Algorithms for Very Large Databases
WG '88 Proceedings of the 14th International Workshop on Graph-Theoretic Concepts in Computer Science
Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
Survey of graph database performance on the HPC scalable graph analysis benchmark
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
A Comparison of Current Graph Database Models
ICDEW '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering Workshops
LinkBench: a database benchmark based on the Facebook social graph
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
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Graphs have become an indispensable tool for the analysis of linked data. As with any data representation, the need for using database management systems appears when they grow in size and complexity. Associated to those needs, benchmarks appear to assess the performance of such systems in specific scenarios, representative of real use cases. In this paper we propose a microbenchmark based on social networks. This includes a data generator that synthetically creates social graphs, and a set of low level atomic queries that model parts of the behavior of social network users. In order to understand how different data management paradigms are stressed, we execute the benchmark over five different database systems representing graph (Dex and Neo4j), RDF (RDF-3X) and relational (Virtuoso and PostgreSQL) data management. We conclude that reachability queries are those that put all the database systems into more difficulties, justifying themselves, and making them good candidates for more complex benchmarks.