LinkedIn recently published how LIquid, its graph database, automates the indexing and real-time access of all connections to members, schools, skills, companies, positions, jobs, events, etc.

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data.

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

But the Microsoft Graph and LinkedIn aren’t Microsoft’s only graphs with APIs: Dynamics 365 has the Common Data Service, a way of describing standard items in a business.

A graph database architecture mirrors sketching on a whiteboard, storing all the information in nodes (representing entities, people and concepts) with relevant context and connections between them.

LinkedIn has a large team working on a proprietary graph database, which sits at the center of nearly every operation at LinkedIn. Twitter depends on a graph database, and has released FlockDB, a ...

Graph databases are a key ingredient in the secret development sauce that makes mega-websites such as Facebook, Google, LinkedIn and others like them work so fast and accurately.

As data complexity continues to grow and the demand for real-time insights increases, the move away from traditional relational databases and towards the adoption of graph databases will become vital.

This new database supports a graph query interface compatible with ISO GQL (Graph Query Language) ... Linkedin 26K Followers. RSS 19K Readers. X 57.1k Followers. Facebook 21K Likes. Bluesky New.