Over the last decade, digital twin technology has gained increasing interest in various fields, such as industrial engineering and manufacturing, healthcare, transportation, energy, logistics, or city operations. While digital twins of single assets dominated in the beginning, we are seeing more and more digital twins for systems of assets, where digital twins need to collaborate with other digital twins to accomplish their objectives. As in service-oriented systems, digital twins provide services that can be used by other twins. While in service-oriented systems a service is typically identified by type information, this is not sufficient in digital twin systems, where there may be a large number of service instances of the same type that are not interchangeable. In this paper, we present a proximity model that allows digital twins to specify the required services by so-called neighborhoods, whose definition is based on spatial relationships between client and service instances. This concept not only simplifies service discovery in digital twin systems, but also allows for efficient implementations. To support this, we illustrate how service discovery based on the proposed proximity model can be implemented on top of a spatial DBMS.