KG-ER is a formally defined conceptual schema language for knowledge graphs, with entity, relationship, attribute, tree-pattern key, and hierarchy constraints, targeting representation-independent design across relational, property graph, and RDF systems.
The LDBC Social Network Benchmark
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abstract
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 this, LDBC SNB uses the recognizable scenario of operating a social network, characterized by its graph-shaped data. LDBC SNB consists of two workloads that focus on different functionalities: the Interactive workload (interactive transactional queries) and the Business Intelligence workload (analytical queries). This document contains the definition of both workloads. This includes a detailed explanation of the data used in the LDBC SNB, a detailed description for all queries, and instructions on how to generate the data and run the benchmark with the provided software.
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The KG-ER Conceptual Schema Language
KG-ER is a formally defined conceptual schema language for knowledge graphs, with entity, relationship, attribute, tree-pattern key, and hierarchy constraints, targeting representation-independent design across relational, property graph, and RDF systems.