Several graph databases rely on a SQL engine and use a table to store the graph data. Others store data in a key-value store or a document-oriented database, making them fundamentally NoSQL.

Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

At the recent Cloud Next conference in Tokyo, Google announced Spanner Graph, a managed feature that integrates graph, relational, search, and AI capabilities within Spanner. This new database ...

Advantages of graph database fraud detection applications The advent of production-quality and highly scalable fraud detection applications that rely on the advantages of machine learning and a ...

But to developers, the Microsoft Graph is exposed as an API to write apps against, not a database. In this case, Microsoft models all the data, developers can just run and go play with it.

To some extent, that goes for all data management systems. More so for graph databases. Even more so for blockchain-based systems. Fluree combines a graph database with blockchain.

Moving to graph database methods for these complex, multi-table queries is a more cost-effective option in many cases, saving time and money over simply scaling the resources.

Overall, the team found tables to be a rich source of novel entities that should be contained in a knowledge graph. Compared to other sources of new entities, such as news stories and social media ...

Since 2012, the Knowledge Graph has been Google’s semantic database, in which the world’s knowledge about entities (nodes) and their relationships to one another (edges) is recorded and ...