Graph data modeling and querying arises in many practical application domains such as
social and biological networks where the primary focus is on concepts and their …

Machine learning is increasingly applied in high-stakes decision making that directly affect
people's lives, and this leads to an increased demand for systems to explain their decisions …

We study the problem of finding and monitoring fixed-size subgraphs in a continually
changing large-scale graph. We present the first approach that (i) performs worst-case …

Datasets and workloads of popular applications that use graph database management
systems (GDBMSs) require a set of storage and query processing features that RDBMSs do …

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

Recently there emerge many distributed algorithms that aim at solving subgraph matching at
scale. Existing algorithm-level comparisons failed to provide a systematic view of distributed …

This paper introduces LMFAO (Layered Multiple Functional Aggregate Optimization), an in-
memory optimization and execution engine for batches of aggregates over the input …

Data provenance has evolved from a niche topic to a mainstream area of research in
databases and other research communities. This article gives a comprehensive introduction …

The Linked Data Benchmark Council's Social Network Benchmark (LDBC SNB) is an effort
intended to test various functionalities of systems used for graph-like data management. For …

Over the last decade, worst-case optimal join (WCOJ) algorithms have emerged as a new
paradigm for one of the most fundamental challenges in query processing: computing joins …