1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.DB2017★ 1 cited
Loom: Query-aware Partitioning of Online Graphs
Hugo Firth, Paolo Missier, Jack Aiston
As with general graph processing systems, partitioning data over a cluster of machines improves the scalability of graph database management systems. However, these systems will in…
cs.DB2016
TAPER: query-aware, partition-enhancement for large, heterogenous, graphs
Hugo Firth, Paolo Missier
Graph partitioning has long been seen as a viable approach to address Graph DBMS scalability. A partitioning, however, may introduce extra query processing latency unless it is sen…