In the era of big data, the single-write multi-read process with separate storage and computing architectures can no longer meet the demands for efficient reading and writing of massive datasets. Multiple computing nodes providing write services concurrently can also cause cache inconsistencies. Some studies have proposed a global ordered transaction log to detect conflicts and maintain data consistency for the whole system using broadcast and playback of the transaction log. However, this scheme has poor scalability because it maintains the global write log at each write node. To solve this problem, this paper proposes a partition-based concurrency control scheme, which reduces the transaction log maintained by each write node by partitioning, and effectively improves the system’s overall expansion ability.