Graph databases are revolutionizing fraud detection in real-time transactions by providing the ability to analyze behaviors and understand subtle relationships between data points, allowing for more effective identification and mitigation of new and evolving types of fraud. PayPal's bespoke graph solution, which predates Aerospike Graph, demonstrated the power of graph technology in detecting and preventing online fraud, with a focus on using temporal graphs to signify high fraud risk and devising a graph query service to retrieve results quickly enough to be used in real-time AI models. The use of graph databases can add context to transactions by coordinating questions about relationships between data points, such as customer behavior and transaction history, making it easier to determine the legitimacy of transactions and keep fraudsters at bay.