FluteDB: An efficient and dependable time-series database storage engine

Abstract

Recently, with the widespread use of large-scale sensor network, time-series data is vastly generated and requires to be processed. Those traditional databases, however, show their limitations in storage when handling such a large stream data. Besides, the actual dependability of databases are also difficult to be guaranteed. In this paper, we present FluteDB, an efficient and dependable time-series database storage engine, which is composed of multiple time-series enhanced sub-modules. The validations of all sub-modules have demonstrated that our improved strategies significantly outperform the existing methods in real time-series environment. Meanwhile, the complete FluteDB utilizes various measures to guarantee its dependability and achieves a higher overall storage efficiency than the state-of-the-art time-series databases.