Recently, there has been a pressing need to manage high-dimensional vector data in data
science and AI applications. This trend is fueled by the proliferation of unstructured data and …

As graph databases become widespread, the International Organization for Standardization
(ISO) and International Electrotechnical Commission (IEC) have approved a project to create …

Abstract GQL (Graph Query Language) is being developed as a new ISO standard for graph
query languages to play the same role for graph databases as SQL plays for relational. In …

We report on a community effort between industry and academia to shape the future of
property graph constraints. The standardization for a property graph query language is …

The Social Network Benchmark's Business Intelligence workload (SNB BI) is a
comprehensive graph OLAP benchmark targeting analytical data systems capable of …

Graph databases (GDBs) are crucial in academic and industry applications. The key
challenges in develo** GDBs are achieving high performance, scalability …

We propose techniques to evaluate regular path queries (RPQs) over labeled graphs (eg,
RDF). We apply a bit-parallel simulation of a Glushkov automaton representing the query …

The emergence of novel hardware accelerators has powered the tremendous growth of
machine learning in recent years. These accelerators deliver incomparable performance …

We introduce a time-and space-efficient technique to solve regular path queries over
labeled (RDF) graphs. We combine a bit-parallel simulation of the Glushkov automaton of …

Abstract Regular Path Queries (RPQs), which are essentially regular expressions to be
matched against the labels of paths in labeled graphs, are at the core of graph database …