You can think of a graph database as a set of interconnected circles (nodes) and each node represents a person, a product, a place or ‘thing’ that we want to build into our data universe.

Graph databases store information as nodes and data specifying their relationships with other nodes. They are proven architectures for storing data with complex relationships.

This means that, especially towards the end of the 2010s, graph database vendors are increasingly taking advantage of GPUs to traverse and compare node values along these graphs, effectively ...

Graph databases are the fastest-growing category in all of data management. Graph databases have evolved into a mainstream technology that has been successfully implemented by organizations in ...

Graph database vs. relational database. In a traditional relational or SQL database, the data is organized into tables. Each table records data in a specific format with a fixed number of columns ...

At the recent NODES Developer Expo and Summit sponsored by Neo4j, a leading vendor of graph database software, I spoke with Dr. Jim Webber, the Chief Data Scientist at Neo4j about future hardware ...

Unlike relational databases, which work particularly well with structured data, graph databases are designed to model and store data as interconnected nodes and relationships.

The Global Graph Database Market size is expected to reach $8.1 billion by 2028, rising at a market growth of 22.2% CAGR during the forecast period.A graph database is a single-pu ...

A graph database is different from a traditional relational database in how it is structured. Instead of using rows and tables to organize data, a graph database has nodes and edges to build out a ...