Alzheimer’s disease (AD) is a neurological disorder that is progressive and characterized by gradual degeneration of brain cells. This disease results in the decline of cognition, memory, and behavior. According to the National Institute of Aging, AD is currently ranked 7^th leading cause of death in the U.S. Our research objective is to review existing computational methods and databases for further AD research. The paper starts with a brief introduction about AD, computational methods and databases. The computational methods focus on Molecular Dynamic (MD) Simulation and Machine Learning models. The next section talks about clinical and scientific databases including International Alzheimer’s and Related Dementias Research Portfolio and the National Alzheimer’s Coordinating Center amongst others. These databases are classified into different categories such as biomarkers, genetic research, and many other categories. In the application section, this paper introduces applications related to AD treatment, early detection, and progression. This research aids medical professionals, researchers, and pharmaceutical companies with valuable data to improve AD research and treatment.