A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...

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 ...

Social graphs are a prime example of utilizing the graph model, Xu was working at Twitter till 2011, and the graph databases that were around at the time could not cope.

For example, LDBC collaboration has helped drive standardization of the graph data model and query languages. This standardization helps ease the definition of benchmarks and is valuable to users ...

A new semantic-based graph data model has emerged within the enterprise. This data model has all of the advantages of the relational data model, but goes even further in providing for more ...

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.

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

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 ...

Aerospike Inc., maker of a highly scalable NoSQL database, today is entering the graph database market with an offering that it claims can outperform and outscale offerings from market leaders ...

One example would be making connections between data collected from a patient’s various doctors and pharmacies. Why Graph Analytics is Important for Healthcare Hospitals deal with stockpiles of ...