Databases are growing steadily, and distributed computer systems are more and more easily available. This provides an opportunity to satisfy the increasingly tighter efficiency requirements by means of distributed data structures. The design and analysis of these structures under efficiency aspects, however, has not yet been studied sufficiently. To our knowledge, a single scalable, distributed data structure has been proposed so far. It is a distributed variant of linear hashing with uncontrolled splits, and, as a consequence, performs efficiently for data distributions that are close to uniform, but not necessarily for others. In addition, it does not support queries that refer to the linear order of keys, such as nearest neighbor or range queries. We propose a distributed search tree that avoids these problems, since it inherits desirable properties from non-distributed trees. Our experiments show that our structure does indeed combine a guarantee for good storage space utilization with high query efficiency. Nevertheless, we feel that further research in the area of scalable, distributed data structures is dearly needed; it should eventually lead to a body of knowledge that is comparable with the non-distributed, classical data structures field.