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 ...

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.

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.

This is the numerical data that people have presented as graphs and tables and charts. For example, the data could be a graph in a PDF report, or a table in an Excel spreadsheet, or a barchart ...

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.

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 ...

Use a relational database for it,” said Emil Eifrem, Neo’s CEO. “But if you have data that is messy, that is complex, that is connected, then a graph database is vastly superior.” ...

If your table rows tend to be sparsely populated, and your queries tend to involve heavily nested joins, then a graph database is probably right for you—and Neo4j would be an excellent choice.

The graph database seemed to be the right match, since the data had the complex connections that would not fit neatly into tables. But he found that developing the application was significantly ...