In the application of stream computing, the mismatch of upstream and downstream data inflow and outflow speed often leads to the problem of insufficient data buffer capacity or overflow backpressure, and data loss and system crash are the possible consequences. A good solution is in urgent need. The existing methods address the downstream backpressure problem by transferring pressure upstream, but in this paper, a backpressure solution based on data migration strategy is proposed to solve the backpressure problem by dispersing the pressure to light-loaded nodes of other branches. The experiments on the NS-3 network simulation platform show that the proposed method has significantly improved the throughput proportion and latency in contrast to the Credit backpressure mechanism of the Flink framework.