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.

By combining ontology and large language model-driven techniques, engineers can build a knowledge graph that is easily queried and updatable.

Bidding to keep its market-leading graph database engine out in front against new competition, Neo Technology Inc. today is unveiling an integration and visualization layer on top of its platform ...

Imagine your database of choice blown out of the water by a startup emerging from stealth. TigerGraph may have done just that for graph databases.

Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

You can easily create a graph in Google Sheets to get a visual representation of your data. Here's how to use Google Sheets to create a graph.

Graph database vendor Neo4j announced today new capabilities for vector search within its graph database. Neo4j’s namesake database technology enables organizations to create a knowledge graph ...

Graph databases offer a more efficient way to model relationships and networks than relational (SQL) databases or other kinds of NoSQL databases (document, wide column, and so on). Lately many ...

The goal of this type of database is to make it easier to discover and explore the relationships in a property graph with index-free adjacency using nodes, edges, and properties.