Data is one of the most valuable assets in today's world and is used in the everyday life of every person and organization. This data stores in a database in order to restore and maintain its efficiently. Since there is a database that can be exploited by SQL injection attacks, internal threats, and unknown threats, there are always concerns about the loss or alteration of data by unauthorized people. To overcome these concerns, there are several security layers between the user and the data in the network layer, host, and database. For instance, security mechanisms, including firewall, data encryption, intrusion detection systems, etc., are usedto prevent infiltration. Database Intrusion Detection System uses a variety of data mining techniques to detect abnormalities and detect malicious and intrusive activities. In this paper, a category of intrusion detection techniques is presented first in the database, and a review of the general algorithms for intrusion detection in databases is demonstrated. Since signature-based methods are elder and less complex and less diverse, the main focus of this paper is on behavioral methods.