In recent years, applications have started using geo-distributed databases, even though their behavior under different workloads remains complex. Therefore, this project analyses how several databases handle transactional workloads using the SmallBank benchmark. We implement and adapt an already existent benchmark, previously used for non-distribuited databases. Furthermore, we use it to evaluate multiple geo-distributed databases highlighting their strengths and weaknesses throughout multiple scenarios designed to stress different parts of the system. We observe that in most scenarios Detock performs slightly better than SLOG, and both outperform Calvin. This aligns with the fact that Detock builds upon SLOG, which itself improves on Calvin. On the other hand, Janus's performance is significantly behind the others due to its communication overhead. However, while the SmallBank benchmark provides an insightful comparison, providing specific advantages compared to previous benchmarks, its adaptation to geo-distributed databases limits its ability to compare scenarios with higher percentages of multi-home and multi-partition transactions.