Understanding the relationships in graph database theory allows us to work with the new 'shape' of data itself. Businesspeople like graphs. C-suite executives are fond of pie charts, Venn diagrams, ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional neural ...

Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...

Fluree is not a very straightforward product to get. To some extent, that goes for all data management systems. More so for graph databases. Even more so for blockchain-based systems. Fluree combines ...

Polyglot persistence is becoming the norm in big data. Gone are the days when relational databases were the one store to rule them all; now the notion of using stores with data models that best align ...

The problem: The app must store a collection of people and who they know. Sometimes it must find out everyone who knows someone who knows Bob. Sometimes it must look further for everyone who is three ...

Forbes contributors publish independent expert analyses and insights. Working on digital transformation by busting boundaries. This article is more than 4 years old. The creator of Bitcoin, Satoshi ...

Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...