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 ...

For example, graph databases excel in environments where relationships drive functionality, offering advantages in developing custom large language models (LLMs) and other advanced AI-driven ...

A property graph database, such as Neo4j’s, is an extreme example of a structured data store. The node-and-edge graph structure excels at helping users to explore knowledge about entities (defined as ...

For example, the team behind their graph database was acqui-hired by Amazon six years ago, which stalled updates on the open source projects. However, this openness also makes it easier to ensure free ...

Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around knowledge graphs, which have become increasingly vital in data intelligence ...

A graph is a data structure that holds not only business records but also information about how those records are connected to one another. For example, it can point out if two purchase logs were ...

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.

Graph database startup TigerGraph Inc. today announced a major update to its flagship cloud platform with the Savanna release, bringing with it six times faster network deployments and dozens of ...

This example generates several graphs of sales data that can be accessed from a single Web page. The graphs are two bar charts of summary sales data and three pie charts that break the data down by ...