• Corpus ID: 210064402

The LDBC Social Network Benchmark

@article{Angles2020TheLS,
  title={The LDBC Social Network Benchmark},
  author={Renzo Angles and J{\'a}nos Benjamin Antal and Alex Averbuch and Peter A. Boncz and Orri Erling and Andrey Gubichev and Vlad Ioan Haprian and Moritz Kaufmann and Josep-Llu{\'i}s Larriba-Pey and Norbert Mart{\'i}nez-Bazan and J{\'o}zsef Marton and Marcus Paradies and Minh-Duc Pham and Arnau Prat-P{\'e}rez and Mirko Spasic and Benjamin A. Steer and G{\'a}bor Sz{\'a}rnyas and Jack Waudby},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.02299}
}
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… 

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References

SHOWING 1-10 OF 33 REFERENCES

Diversified Stress Testing of RDF Data Management Systems

TLDR
This work performs an in-depth experimental analysis that shows existing SPARQL benchmarks are not suitable for testing systems for diverse queries and varied workloads and provides stress testing tools for RDF data management systems, and uses the Waterloo SParQL Diversity Test Suite (WatDiv) to address these shortcomings.

The Anatomy of the Facebook Social Graph

TLDR
A strong effect of age on friendship preferences as well as a globally modular community structure driven by nationality are observed, but it is shown that while the Facebook graph as a whole is clearly sparse, the graph neighborhoods of users contain surprisingly dense structure.

The linked data benchmark council: a graph and RDF industry benchmarking effort

TLDR
An overview of the LDBC project including its goals and organization is presented, and so-called "choke-point" based benchmark development through which experts identify key technical challenges, and introduce them in the benchmark workload is introduced.

An RDF Dataset Generator for the Social Network Benchmark with Real-World Coherence

TLDR
This paper shows that the synthetic RDF dataset used in the Social Network Benchmark is characterized with high-structuredness and therefore modifications to the data generator are introduced so that it produces an RDF datasets with a real-world structuredness.

Beyond Macrobenchmarks: Microbenchmark-based Graph Database Evaluation

TLDR
A novel microbenchmarking framework is introduced that provides insights on graph database systems performance that go beyond what macro-benchmarks can offer, and includes the largest set of queries and operators so far considered.

Fair Benchmarking Considered Difficult: Common Pitfalls In Database Performance Testing

TLDR
A study of the common pitfalls in DBMS performance comparisons is performed, and advice on how they can be spotted and avoided so a fair performance comparison between systems can be made.

An early look at the LDBC social network benchmark's business intelligence workload

TLDR
An early look at the LDBC Social Network Benchmark's Business Intelligence (BI) workload which tests graph data management systems on a graph business analytics workload, designed by taking into account technical "chokepoints" identified by database system architects from academia and industry.

Birds of a feather scam together: Trustworthiness homophily in a business network

The Train Benchmark: cross-technology performance evaluation of continuous model queries

TLDR
The benchmark focuses on the performance of query evaluation, i.e. its execution time and memory consumption, with a particular emphasis on reevaluation, and can be adopted to various technologies and query engines, including modeling tools; relational, graph and semantic databases.

G-CORE: A Core for Future Graph Query Languages

TLDR
G-CORE is reported on a community effort between industry and academia to shape the future of graph query languages, and strikes a careful balance between path query expressivity and evaluation complexity.