Social Network Benchmark Goals


Social Network interaction is amongst the most natural and widely spread activities in the internet society, and it has turned out to be a very useful way for people to socialise at different levels (friendship, professional, hobby, etc.). As such, Social Networks are well understood from the point of view of the data involved and the interaction required by their actors. Thus, the concepts of friends of friends, or retweet are well established …

It is with great pleasure that we announce the new LDBC organisation site at The LDBC started as a European Community FP7 funded project with the objective to create, foster and become an industry reference for benchmarking RDF and Graph technologies. A period of more than one and a half years has led us to the creation of the first two workloads, the Semantic Publishing Benchmark and the Social Network Benchmark in its …

2nd International Workshop on Benchmarking RDF Systems


Following the 1st International workshop on Benchmarking RDF Systems (BeRSys 2013) the aim of the BeRSys 2014 workshop is to provide a discussion forum where researchers and industrials can meet to discuss topics related to the performance of RDF systems. BeRSys 2014 is the only workshop dedicated to benchmarking different aspects of RDF engines - in the line of TPCTC series of workshops.The focus of the workshop is to expose and initiate …

DATAGEN: Data Generation for the Social Network Benchmark


As explained in a previous post, the LDBC Social Network Benchmark (LDBC-SNB) has the objective to provide a realistic yet challenging workload, consisting of a social network and a set of queries. Both have to be realistic, easy to understand and easy to generate. This post has the objective to discuss the main features of DATAGEN, the social network data generator provided by LDBC-SNB, which is an evolution of S3G2 [1].

One of the most …

Getting Started With SNB


In a previous blog post titled “Is SNB like Facebook’s LinkBench?”, Peter Boncz discusses the design philosophy that shapes SNB and how it compares to other existing benchmarks such as LinkBench. In this post, I will briefly introduce the essential parts forming SNB, which are DATAGEN, the LDBC execution driver and the workloads.


DATAGEN is the data generator used by all the workloads of SNB.
we introduced the …

The LDBC Social Network Benchmark (SNB) is composed of three distinct workloads, interactive, business intelligence and graph analytics. This post introduces the interactive workload.

The benchmark measures the speed of queries of medium complexity against a social network being constantly updated. The queries are scoped to a user’s social environment and potentially access data associated with the friends or a user and their friends.

This …