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.

TigerGraph has been touting some benchmarks that compare its performance to several other graph databases (Neo4j, Amazon Neptune, JanusGraph, and ArangoDB) for tests of data loading time and graph ...

There are other native graph databases, which means the data is stored in a graph-like manner and not added on after the fact, as with some graph solutions that reside atop Hadoop and NoSQL. Neo4j is ...

Although a global graph database market estimated at $1.9 Billion in 2021 is expected to grow at 22.5% over the next five years, arguments continue on whether NoSQL graph databases are just ...

The global graph database market size was $2.12 billion in 2022 and is expected to grow to $10.3 billion in 2032, according to estimates from Adroit Research. ... “By design, graph databases are ...

Graph databases excel at answering complex questions about relationships in large data sets. ... Below we will look at these design features and discuss how they work together.

Redwood City, Calif.-based TigerGraph, which bills itself as “the only scalable graph database for the enterprise,” on July 16 launched a version of its cloud product, TigerGraph Cloud, for ...

DataStax, a database vendor that delivers a commercial version of Apache Cassandra, is today announcing that it has acquired Graph database vendor Aurelius. Apache Cassandra is the open source ...

Give me control of a database query language, and I care not who makes its engine. The noticeable spike in interest in graph in the last year can be largely attributed to heavyweights such as ...

Database engine design features. Graph databases from different vendors vary in the technology available as a result of their database engine design choices. Major design features include: ...