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Remote monitoring of patients' biometric data streams offers the possibility to physicians to extend and improve their services to chronically ill patients who are away from medical institutions. This emerging technology is a promising way to address important aspects of the cost issues that most health care systems are experiencing. In order to fulfill its potential, several challenges need to be overcome. First, the data collected needs to be filtered and annotated intelligently to help physicians cope with and navigate the large amount of patient sensor data received as a result of large scale remote health monitoring deployments. Secondly, efficient stream persistence and query mechanisms for these data need to be designed to satisfy health care regulations and help physicians track patient health histories accurately and efficiently. In this paper, we concentrate on the second challenge. We leverage emerging hybrid relational-XML database management systems to design a storage sub-system for remote health monitoring. We evaluate this approach by performing series of performance tests to assess the ability of the proposed system to handle the huge amount of biometric data streams requiring persistence.