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

Inside HR using Neo4j we have already developed the Common Key Tool. Developing tools is very easy using a graph database and that is one of the key advantages of Neo4j as a product.

Graph databases excel for apps that explore many-to-many relationships, such as recommendation systems. Let’s look at an example Jeff Carpenter is a technical evangelist at DataStax. There has ...

My advice is to start trialing graphs, as the investment required to find out if your organization can benefit from using graph databases is quite small—but the potential ROI can be surprisingly ...

Ease-of-use. Graph databases from different vendors vary considerably in the ease-of-use of various parts of their functionality intended for use by the following typical categories of end-users: ...

Graph database use cases. Graph databases work best when the data you’re working with is highly connected and should be represented by how it links or refers to other data, typically by way of ...

The graph database is created using a graph database management system (DBMS) like Neo4j. The Cypher query generated in step 3 is ingested into the DBMS, which creates the nodes and edges in the ...

Using graph databases, you can very easily find patterns in data -- that is very much what we do -- and fraud detection is a lot about finding patterns.

Teradata just released a new type of SQL called SQL-GR, intended to make the graph analytics easy for enterprise users. According to a report by industry observer DB-Engines, “Graph DBMSs are ...

Image: Seventyfour/Adobe Stock. A graph database is all about relationships. Using nodes to store data entities and edges to store relationships between those identities, such databases are often ...