Recent research on distributed database management techniques for wireless sensor networks (WSNs) focuses on improving data storage, retrieval, and query processing efficiency while minimizing energy consumption and communication overhead. These approaches utilize in-network data aggregation, distributed indexing, and replication mechanisms to enable localized data access and fault-tolerant operations across sensor nodes. Advanced models integrate data-centric storage and adaptive query routing to optimize data distribution and reduce latency. Emerging studies also explore AI-driven and blockchain-based frameworks to enhance data consistency, integrity, and scalability in dynamic WSN environments. Overall, distributed database management in WSNs aims to achieve energy-efficient, reliable, and scalable data handling for real-time and large-scale sensing applications.