Especially the most sophisticated fake technology with artificial intelligence (AI) used for the creation of completely convincing fake media has become an unprecedented security threat to database security. In this paper, the increasing threats imposed by deepfakes on database systems are studied specially focusing on the security threat these biometric security measures employed in the form of facial and voice authenticity pose toward them. Security procedures can be easily defeated by deepfakes because they mimic actual users, thereby gaining illicit access to secret data. This paper also provides a brief comparison among several technological interventions supposed to tackle such a threat, including smart detectors based on deep learning, multimodal, and blockchain for securing database trails. The study inquires about the requirement of detection of deepfake videos in real time and also establishes a toll in providing a secure system and how the new technologies can add security to the database. With this, it has been observed that significant advancements have been made in the laboratories with the improvement in algorithms for the detection; however, the escapement of these technologies into ambient spaces has proven problematic. In addition, this paper discusses future development directions for work in this area, including improvement of detection models, the addition of behavior biometrics, and increased hybrid security system integration. Finally, this review points to opportunities to build database systems and introduces protective measures against threats related to the deepfake technology application while advocating for the system's reliability and security.