Previously studies have weakly solved the problem of playing small-board-sized Go, but this study determines a strongly-solved solution and a database to access afterward. State reduction is applied by the features of Go; and then retrograde analysis is used to find the optimal answer of every possible state of small-board-sized Go. Dealing with large state information, an in-memory method is used to search the states for small-board-sized Go. Saving separated compressed data in the memory, instead of on a disk, and decompressing this data on demand, to balance performance and memory usage, in order to solve the problem efficiently. This method can also be applied to large scale data processing. A method is also determined that obtains the optimal result for boards with a single row.