We present two methods for weighted consistent hashing also known as weighted distributed hash tables. The first method, called Linear Method, combines the standard consistent hasing introduced by Karger et al. [9] with a linear weighted distance measure. By using node copies and different partitions of the hash space, the balance of this scheme approximates the fair weight relationship with high probability. The second method, called the Logarithmic Method, uses a logarithmic weighted distance between the peers and the data to find the corresponding node. For distributing one data element it provides perfect weighted balance. To provide this distribution for many data elements we use partitions to achieve a fair balance with high probability. These methods provide small fragmentation, which means that the hash space is divided into at most O (n log n) intervals. Furthermore, there is an efficient data structure that assigns data elements to the nodes in expected time O (log n). If small fragmentation is not an issue one can replace the use of partitions by a method we call double hash functions. This method needs O (n) for assigning elements to a node, yet it can be directly used for Storage Area Networks, where the number of nodes is small compared to participating nodes in Peer-to-Peer networks.