Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

Speaker: Young Han Abstract: The considerable interest in distributed systems that can execute algorithms to process large graphs has led to the creation ... On Improving Distributed Pregel-like Graph ...

A number of graph-parallel processing frameworks have been proposed to address the needs of processing complex and large-scale graph structured datasets in recent years. Although significant ...

As one of the leads, Changwoo Min, tells The Next Platform, even though terascale graph processing is no longer unheard of, finding ways to make it efficient and high performance is where the real ...

While distributed graph processing engines have become popular for processing large graphs, these engines are typically configured with a static set of servers in the cluster. In other words, they ...

Neo4j is not yet a fully distributed graph database, even with 4.0. But with the new multiple database feature – which essentially allows users to shard a single graph database into multiple ...

Sure, there are graph databases like Neo4j, but graph analysis or graph search may be more useful, depending on the sorts of data relationships you need to explore Graph processing is hot right ...

By having a native C++ graph storage engine (GSE) work side-by-side with a graph processing engine (GPE) to handle of data and algorithms and by using parallelism and a distributed architecture.

The company touts its graph database as a distributed, high-availability architecture designed for scalability and fast recovery that is ideal for production environments. NebulaGraph says it can ...