A graph database can help you discover connections in your data you never imagined; here’s how to get started Alaa Mahmoud is an advisory software engineer and master inventor at IBM Analytics Cloud ...

As enterprises continue to navigate the complexities of digital transformation, connected data is becoming an increasingly common necessity. Connected data is when data assets are linked together to ...

Data-hungry AI applications are fed complex information, and that's where graph databases and knowledge graphs play a crucial role. Over the past decade, there has been endless churn in technologies ...

Response time stays predictable. In a relational database, the same check means self-joining an identifier table for each ...

AI, natural language processing and semantic search applications are a driving force behind emerging data management operations. Data teams can use knowledge graphs in conjunction with these tools to ...

Many organizations continue to avoid the additional complexity of graph databases by forcing relationship workloads into relational databases, even though graph databases have been around for decades.

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

Neo4j, the graph database from the US-Swedish company of the same name, is used by 76% of the Fortune 100, and its Australian customers include organisations in the healthcare, policing and banking ...

The main objective of NoSQL databases is improved efficiency. It is somewhat achieved with the use of new technologies and thinking outside the box. An example of the new technologies applied could be ...