Federated processing of queries over RDF data sources offers significant potential when a SPARQL query cannot be answered by a single data source alone. However, finding efficient plans to execute a queryover a federation is challenging, especially if different federation members provide different types of data access interfaces. Different interfaces imply different request types, different forms of responses, and different physical algorithms that can be used, each of which consumes varying amounts of resources during query execution. This heterogeneity poses additional obstacles to the task of planning query executions, in addition to the inherent complexity arising from numerous possible join orderings andvarious physical algorithms. As a first step to address these challenges, we propose a cost model that captures the resource requirements of different operators depending on the type of federation member,allowing us to estimate cost of a given query execution plan without actually executing it. To evaluate our approach, we conduct experiments on FedBench with our cost model and compare it to the current state-of-the-art approach to query planning for heterogeneous federations of RDF data sources.