AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Anyone who's ever tried to build distributed applications (dApps) on the (Ethereum) blockchain would concur: Although blockchains are conceptually quite close to databases, querying databases feels ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Graph databases are playing a growing role in improving fraud detection, ...

Graph technology has become a requirement for the modern enterprise. Companies in virtually every industry, from healthcare to energy to financial services, are applying the power of graph analytics ...

Graph databases excel for apps that explore many-to-many relationships, such as recommendation systems. Let’s look at an example Jeff Carpenter is a technical evangelist at DataStax. There has been a ...

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 ...

Debate and discussion around data management, analytics, BI and information governance. This is a guest blogpost by Neo4j co-founder and CEO Emil Eifrem, who explains why his sector needs its own ...