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

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

Writing complex data structures in Go can help developers better understand the principles of pointers and references.

After relational, key-value, document, columnar, and time-series databases, the latest link in this evolutionary proliferation of data structures is graph.

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. But graphs are also ...

Informatica's Gaurav Pathak and Fivetran's George Fraser discussed the evolving data stack and the role of metadata knowledge graphs during Supercloud 7.

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 ...

The four pillars of graph adoption This confluence of graph analytics, graph databases, graph data science, machine learning, and knowledge graphs is what makes graph a foundational technology.