MongoDB is a Document based NoSQL that developed to answer the increasing demands for scalable date store in big data era. To achieve good performance, the system must be designed properly from the start. The performance issues like hotspot can be fatal to overall performance and various researches were focusing on applying load balancing techniques to resolve this problem. However, these techniques may not be effective for time series data, such as real-time system logs. In this paper, we propose a new data distribution algorithm based on tag aware sharding to minimize the effect of hotspot problem, especially the system with heavy writing requirements. This improves the overall performance and allow us to handle time series data effectively.