Rainbow: A distributed and hierarchical RDF triple store with dynamic scalability

Rong Gu, Wei Hu, Yihua Huang
2014 2014 IEEE International Conference on Big Data (Big Data)  
In the Big Data era, the ever-increasing RDF data have reached a scale in billions of triples and brought obstacles and challenges to single-node RDF data stores. As a result, many distributed RDF stores have been emerging in the Semantic Web community recently. However, currently published ones are either not enough efficient on performance or failed to achieve flexible scalability. In this paper, we propose Rainbow, a scalable and efficient RDF triple store. The RDF data indexing scheme in
more » ... nbow is a hybrid one which is designed based on the statistical analysis of user query space. Further, to better support the hybrid indexing scheme, Rainbow adopts a distributed and hierarchical storage architecture that uses HBase as the scalable persistent storage and combines a distributed memory storage to speedup query performance. The RDF data in memory storage is partitioned by the consistent hashing algorithm to achieve the dynamic scalability. Experiments show that Rainbow outperforms typical existing distributed RDF triple stores, with excellent scalability and fault tolerance.
doi:10.1109/bigdata.2014.7004274 dblp:conf/bigdataconf/GuHH14 fatcat:mxi5hq657vfrpn6gbyr6hsunyi