Getting Your Data Graph-Ready After deciding on the technology and the key operational and logistical questions you want to answer with graph, your next step is to build a graph data model.

Understand the building blocks of knowledge graphs – entities, relationships and attributes – and how they relate to information retrieval.

In the new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. Here's a shortlist of technologies ...

Companies traveling the long road to becoming data-driven organizations should take a close look at why Graph Databases are taking master data management to a new level.

Graph data modeling requires a different paradigm than modeling with Relational or other NoSQL databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling with Graph databases.

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

Historians are electronic data recording products that are typically used for trend style data. Trend data is comprised of measurement samples over a period of time. Prior to automation of this data ...

A hitherto under the radar graph database that uses blockchain to support data lineage and verification wants to take over the world, starting with the US Department of Defense ...

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.

Graph database startup Neo4j raised $320 million at an over $2 billion valuation, highlighting the value of graph databases.