The graph database was originally designed to store networks — that is, the connections between several elements such as people, places they might visit, or the things they might use.

Graph databases work best when the data you’re working with is highly connected and should be represented by how it links or refers to other data, typically by way of many-to-many relationships.

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

The Bulgarian graph database startup Graphwise today announced a major upgrade to its flagship GraphDB tool, adding new features aimed at boosting enterprise knowledge management and creating a more ...

Aerospike this week rolled out new graph database offering that leverages open source components, including the TinkerPop graph engine and the Gremlin graph query language. The NoSQL company foresees ...

Global Graph Database Market Global Graph Database Market Dublin, Dec. 13, 2023 (GLOBE NEWSWIRE) -- The "Global Graph Database Market by Model Type (RDF, LPG, Hypergraph), Offering (Solutions ...

Neo4j, which commands 44% of the graph database market (per a Cupole Consulting Group report) and counts 84% of the Fortune 100 as customers, including IBM and Walmart, plans to add even more AI ...

Graph databases focus on the relationships within the data and, more importantly, can reveal relationships you might not have known existed.

Graph databases enable investigators to store detailed patterns of problematic actors. Then, they can query the data to uncover intricate connections between the suspicious actor and other entities.

Image: Seventyfour/Adobe Stock. A graph database is all about relationships. Using nodes to store data entities and edges to store relationships between those identities, such databases are often ...