Personalized support for learners became even more important when e-learning take place in distributed database system. This research provides access to learning resources in a distributed e-learning database and it intends to adapt the system to the learner's needs (personal needs) so that each learner gets the idea that the system was created just for him and knows what he likes. The personal needs are determined in different ways like the current request (search), the previous resource requests (personal search about the previous requests) or the education level of the learner (syllabus). The personal search methods are implemented by creating explicit and implicit user profiles to store the learner's information and his previous resource requests (interest). The personalization techniques that are used in this research are content-based filter and rule-based filter which have rely heavily on user profiles. The proposed system ensuring security in terms of authentication (identify the user and his permission), integrity (the data is not getting changed or corrupted), and confidentiality (other people should not be able to see other user's personal information in the user profile). The proposed system architecture is Two-Tier Multiple-Client / Multiple-Server model which consist of two data servers and multiple clients. Each server used to store a fragment of the data. The servers are located in locations where there data are most widely used to decrease the size of the data stored in each server, decrease the load over the distributed database management system and most operations are performed locally.