Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

For a few decades, structured data are typically arranged as relational tables and stored in relational databases. Recent years have witnessed the blossom of graph databases, for which graph becomes ...

Unlike relational database systems which represent data as elements in tables, graph database systems represent them as nodes which are related to each other. In graph databases, each node of the ...

In a graph database, similar pieces of data are connected directly to one another through common attributes. Relationships are “first-class citizens” in graph databases, unlike in relational databases ...

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

We had a chance to speak with TigerGraph's incoming head of product R&D, and it spurred some thoughts on where we thought graph databases should go.

Doing this in a relational database structure is pretty painful. In the JPA/SQL version of granny, I need two tables and multiple trips to the database just to walk the graph of relationships.

Emerging graph database benchmarks are already helping to overcome performance, scalability and reliability issues.

What does graph database actually mean? Find out inside PCMag's comprehensive tech and computer-related encyclopedia.

Graph-relational database developer EdgeDB Inc. is gearing up for prime time after closing on a $15 million early-stage round of funding ahead of its official launch early next year.