In this video from the PASC16 conference, Andrew Lumsdaine from Indiana University presents: Context Matters: Distributed Graph Algorithms and Runtime Systems. “The increasing complexity of the ...

A new framework called Falcon, developed by Unnikrishnan Cheramangalath, is revolutionizing graph analytics. This domain-specific language simplifies complex computations across diverse computing ...

Users can build visual graphs that display the relationships in graph databases, display tables of properties, manage queries, connect to SPARQL Endpoints, and build SPARQL or Prolog queries as visual ...

Distributed algorithms for graph problems represent a vibrant area of study that addresses the challenges of decentralised computation across interconnected networks. By partitioning complex graph ...

Today we dive deeper into the differences between centralized and distributed performance optimization solutions. The technical functions that Centralized and Distributed ADS solutions perform are ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...

Efficiently and quickly chewing through one trillion edges of a complex graph is no longer in itself a standalone achievement, but doing so on a single node, albeit with some acceleration and ...

Graph algorithms and processing form the backbone of numerous applications across science and industry, ranging from social network analysis to large-scale data management. The field has evolved to ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...