Abstract: The space solar energy development and utilization is gradually becoming a reality. In the process of energy transfer from space to the ground， losses are inevitable. If those lost energy could be effectively utilized in space， the efficiency of energy utilization in SSPS（Space Solar Power Station）would be significantly improved. The “Space Computing Project” concept is proposed-a lightweight， large-power， and high-efficiency data processing center is established in space， and the electric energy generated by SSPS is directly used to calculate spatiotemporal data from satellites or other data sources. Providing the highest possible underlying data capability support under limited hardware resources is an engineering challenge that must be solved during the implementation of the Space Computing Project. Currently， there are few effective solutions. The “Soft Supercomputing” platform is designed. This platform is based on a high-performance real-time database software called NoSQLt. It is hardware-independent and with a small size. By using the high-concurrency and high-throughput data support capabilities provided by NoSQLt， the hardware computing capability can be fully utilized， so as to achieve efficient data processing ability with limited hardware resources deployed in space. Many application cases based on NoSQLt have proved the feasibility of Soft Supercomputing platform. For numerical data， a concurrent throughput of 5.3 million transactions per second is implemented on a regular desktop platform， and 1.15 million transactions per second on the Raspberry Pi 4B platform. A new data center energy consumption evaluation index called “Unit Throughput Capacity” is proposed.Performance testing experiments prove that NoSQLt has high performance under limited hardware resources， providing a fundamental capability guarantee for the future implementation of Space Computing Project.

Key words: space solar power station, Space Computing Project, database, spatiotemporal data, Soft Supercomputing