We have designed, implemented and evaluated a resource adaptive distributed information sharing system where automatic adjustments are made internally in our information sharing system in order to cope with varying resource consumption. CPU load is monitored and a light-weight trigger mechanism is used to avoid overload situations on a per-machine basis. Additional improvements are obtained by calculating what we call a utility score to better determine how the data structures in the system should be arranged. Our results show that resource adaptation is an efficient way of improving query throughput, and that it is most effective when the number of stored data items in the system is large or many queries are performed concurrently. By applying resource adaptation, we are able to significantly improve the performance of our information sharing system.