The Log-Structured Merge Tree (LSM Tree) is widely employed in key-value stores, ensuring efficient database read performance at the expense of increased write stall. While this stall enhances read performance, it notably degrades write efficiency. This paper examines the write stall phenomenon in LSM Tree-based key-value stores and proposes a solution: Key Space Partitioned RocksDB. This architecture comprises a MemTable backed by Storage DRAM, the Key Space Partitioned MemTable, and the Key Space Partitioned LSM Tree. Key Space Partitioned RocksDB demonstrates a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.7\times$</tex> enhancement in YCSB-A throughput compared to conventional RocksDB, a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$3.5\times$</tex> reduction in average GET(key) latency, and a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.2\times$</tex> decrease in average PUT (key, value) latency.