Fraud is a significant threat across various industries, leading to an increased demand for real-time detection systems as traditional after-the-fact methods become inadequate. The global market for fraud detection solutions is anticipated to grow substantially, driven by the need for businesses to safeguard customer experience, prevent financial losses, and quickly adapt to emerging threats. Real-time fraud detection involves analyzing transactions instantly to identify suspicious activities, leveraging advanced technologies such as machine learning, AI, and graph analysis to enhance detection accuracy and scalability. Challenges include achieving ultra-low latency, managing large data volumes, and balancing accuracy with customer friction. Companies like Aerospike offer high-performance database platforms that support real-time data processing, enabling organizations to effectively integrate and analyze diverse data sources, thereby maintaining robust, agile fraud prevention systems capable of handling evolving threats and maintaining operational efficiency.