# The LDBC Social Network Benchmark

arXiv: https://arxiv.org/abs/2001.02299 · HTML: https://mlsanity.com/paper/2001.02299/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jan 2020.

## Built on by (most cited first, 3 of 3)

- [Intelligent Software Web Agents: A Gap Analysis](https://mlsanity.com/paper/2102.06607/) (2021)
- [BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs](https://mlsanity.com/paper/2306.13814/) (2023)
- [Graph Memory for LLM Agents: At What Cost? A Comparative Evaluation of Query, Ingest, and Update Performance Across Graph Database Engines](https://mlsanity.com/paper/2609.23315/) (2026)

## Abstract (arXiv)

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.