Real-Time Anomaly Detection in Database Workloads

Design an advanced anomaly detection system for database workloads that uses machine learning to identify potential security threats, performance degradation, and unusual access patterns. Develop a solution that implements unsupervised learning algorithms, creates dynamic baseline models, generates actionable alerts, and supports adaptive threat response mechanisms. Include considerations for minimizing false positives and maintaining low-overhead monitoring.