Graph processing is the method of analyzing and manipulating data represented as nodes and relationships. It involves operations such as traversing connections, finding paths, identifying communities, detecting patterns, and calculating relationships between entities. By working directly with the structure of connected data, graph processing can uncover relationships that may be difficult to identify using conventional data-processing methods.
Graph processing is used in social networks, fraud detection, recommendation systems, transportation networks, cybersecurity, knowledge graphs, and scientific research. Large graphs can be processed using specialized algorithms and distributed computing systems, allowing organizations to analyze millions or billions of interconnected entities efficiently
