Persistent memory has excellent characteristics such as non-volatility, byte-addressable, fast random read and write speed, low energy consumption, and large scalability, which provides new opportunities for big data storage and processing. However, the problem of crash consistency of persistent memory systems poses challenges to its widespread application. Existing research work on crash consistency guarantee usually takes extra read and write as the cost, which has a certain impact on the performance and lifetime of persistent memory systems in the time and space dimensions. To reduce this impact, an endurance aware out-of-place update for persistent memory(EAOOP) is proposed. Through software transparent out-of-place update technology, endurance aware memory management is provided for persistent memory, and data is alternately refreshed to the original data region and the updated data region. EAOOP not only guarantees the system’s crash consistency but also avoids redundant data merging operations. At the same time, to efficiently use the memory space, a lightweight garbage collection is performed in the background to process the old data in the updated data region, reducing extra write amplification and bandwidth occupation, thereby further reducing the impact on the lifetime and performance of the persistent memory. Evaluations show that EAOOP has higher performance and less overhead compared with existing work. Among them, the transaction throughput is increased by 1.6 times, and the critical path latency and the write number are decreased by 1.3 times.