RotaryDS: Fast Storage for Massive Data Streams Via a Rotation Storage Model

In this paper, we propose RotaryDS to provide fast storage service for massive data streams. RotaryDS uses a rotation storage model, which employs distributed data buckets to accept highly-arriving data streams. All data buckets have a state, i.e., they can be in the state of data idle waiting, data filling, write waiting, and data dumping. The state of a data bucket is changed according to the data operations. With the rotation storage model, we distribute massive data streams among multiple data buckets, thereby improving the write throughput of the storage system. We implement RotaryDS based on the rotation storage model and conduct preliminary experiments to compare it with MongoDB. The results suggest the efficiency of our proposal.