A new kind of cloud service, called Database-as-aservice (DaaS), provides a novel paradigm which allows data to be stored in remote databases. The types of database used in remote sites can be divided into two categories: Relational Databases (RDB) and NoSQL. NoSQL databases store data in a flexible format, and without schema, so NoSQL databases can be easily scaled across multiple devices. Because of the advantages of the NoSQL databases, many large data applications use NoSQL databases as the backend data management system. Because NoSQL databases usually access the stored data as files, through a distributed file system, the problem of decentralized data management is critical in NoSQL databases. In order to address this issue, many energy-efficient algorithms for file placement are used in distributed file systems. However, these energy-efficient algorithms only focus on reducing the power consumption of storage systems and they ignore the cost of data reliability, which is affected by frequently setting the disk status to standby mode. To maintain data reliability, energy-efficient storage systems usually combine framework of power conservation and a fault tolerance mechanism. However, most developers of energy-efficient frameworks do not consider whether the fault tolerance mechanism can avoid data loss when this combination is used for energy-efficient storage systems. This study proposes a general energy-efficient framework that can be integrated different fault tolerance mechanisms. The experimental results show that the capability of the proposed framework with different erasure code algorithms.