LDBC and Apache Flink


Apache Flink [1] is an open source platform for distributed stream and batch data processing. Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams. Flink also builds batch processing on top of the streaming engine, overlaying native iteration support, managed memory, and program optimization.

Flink offers multiple APIs to process data …

The number of datasets published in the Web of Data as part of the Linked Data Cloud is constantly increasing. The Linked Data paradigm is based on the unconstrained publication of information by different publishers, and the interlinking of web resources through “same-as” links which specify that two URIs correspond to the same real world object. In the vast number of data sources participating in the Linked Data Cloud, this information is not …

In this post we will look at running the LDBC SNB on Virtuoso.

First, let’s recap what the benchmark is about:

  1. fairly frequent short updates, with no update contention worth mentioning

  2. short random lookups

  3. medium complex queries centered around a person’s social environment

The updates exist so as to invalidate strategies that rely too heavily on precomputation. The short lookups exist for the sake of realism; after all, an …

SNB and Graphs Related Presentations at GRADES '15


Next 31st of May the GRADES workshop will take place in Melbourne within the ACM/SIGMOD presentation. GRADES started as an initiative of the Linked Data Benchmark Council in the SIGMOD/PODS 2013 held in New York.

Among the papers published in this edition we have “Graphalytics: A Big Data Benchmark for Graph-Processing Platforms”, which presents a new benchmark that uses the Social Network Benchmark data generator of LDBC (that can …

SNB Interactive Part 2: Modeling Choices


​SNB Interactive is the wild frontier, with very few rules. This is necessary, among other reasons, because there is no standard property graph data model, and because the contestants support a broad mix of programming models, ranging from in-process APIs to declarative query.

In the case of Virtuoso, we have played with SQL and SPARQL implementations. For a fixed schema and well known workload, SQL will always win. The reason for this is that …