Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

Graphs -- data structures that show the relationship among objects -- are highly versatile. It's easy to imagine a graph depicting a social media network's web of connections.

This graph-shaped amalgamation of data points, relationships, metadata, and meaning is what we call a knowledge graph. Google introduced the term in 2012, and it’s now used far and wide.

This makes data structures one of the most fundamental components of computer science, and this is why they are at the core of all subfields, including data systems (relational, key-value, graph ...

Choosing a graph database for a particular application depends on several factors, including the complexity of data relationships, scalability requirements, performance needs, and functionalities ...

Graphs -- data structures that show the relationship among objects -- are highly versatile. It's easy to imagine a graph depicting a social media network's web of connections.

The concept of blockchain as a standalone technology started gaining popularity in 2015. Prior to that, it was just known as a data structure underlying Bitcoin technology. In Satoshi Nakamoto’s ...