A storage model of temporal knowledge graph combining snapshot and log modes, which was called SL-tgStore, was proposed, in order to solve the storage problem of temporal knowledge graph. The model was consisted of several time buckets, and each time bucket was composed of a series of time windows. The initial snapshot was introduced by the first time window as the basic unit of temporal knowledge graph storage and processing, and it was stored as an incremental log in the following time window. The corresponding threshold was proposed to determine the generation of the initial snapshot, that is, a new time bucket was generated to achieve the balance between the number of initial snapshots and the number of incremental logs, and a temporary snapshot generation algorithm was proposed. The proposed model can effectively solve the problems of large memory consumption in snapshot storage mode and low query efficiency in log storage mode. Four index structures were proposed on this basis, in order to query the SL-tgStore model efficiently. Experiments were carried out on four real datasets, and the theoretical and experimental results showed that the proposed SL-tgStore storage model was efficient.