Within data centers, many applications rely on a uniform total order broadcast algorithm to achieve load-balancing or fault-tolerance. In this context, achieving high throughput for uniform total order broadcast algorithms is an important issue: It contributes to optimize data center resources usage and to reduce its energy consumption. This paper presents TRAINS , a throughput-efficient uniform total order broadcast algorithm. The paper estimates T RAINS performance. It evaluates the prediction-oriented throughput efficiency (POTE) - i.e. the theoretical ratio between bytes delivered and bytes transmitted on the network. TRAINS POTE improves the POTE of the best algorithm of the literature. For 5 processes, the POTE improvement reaches a peak of 250% for 10 bytes messages. Experimental evaluation confirms T RAINS high throughput capabilities. The trade-off of this throughput improvement is the alteration of the latency. The worst alteration is in the case of 2 processes: 125%