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 ...

Graphs are a natural fit for modeling concepts used in solving diverse problems in science, commerce, engineering, and governance. Responding to the variety of graph data and algorithms, many parallel ...

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 ...

Neo4j is the leader in the burgeoning graph database market, with 17 years in development and thousands of open source users. But the database has a hard limit in terms of scalability, since it ...

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 ...

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 ...

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.