Multi-tenant transactional databases frequently observe contention on shared data, leading to a need for performance isolation. Databases typically provide performance isolation via a request rate limit or quota per tenant, but this approach can lead to system underutilization. Traditionally, fair sharing has been applied to achieve both performance isolation and high utilization in other domains. In this paper, we address the problem of fair sharing for transactions, which introduces new challenges because client requests do not acquire resources all at once. We propose DRFT, the first fair transaction scheduling algorithm that ensures both the share guarantee and strategy-proofness by accurately accounting for transactional resource usage. We evaluate DRFT on a range of standard benchmarks and real-world workloads, showing that it ensures fairness with less than a 5% throughput overhead compared to state-of-the-art scheduling policies.