With the increase of massive data, a large number of business applications began to seek effective and scalable frameworks for data storages and processing. Under this background, emerging technologies for big data, such as Hadoop-based systems that use scalable distributed storage system HBase, become available. Since most of business data nowadays are stored in relational databases, and information imprecision and uncertainty widely exist in real-world applications, there is an increasing willingness to manage large-scale fuzzy relational data in the Hadoop-based platform. This paper concentrates on fuzzy information modeling in HBase. In particular, we investigate the formal transformation from the fuzzy relational data model to the HBase model and develop a set of mapping rules to assist in the transformation process. In addition, we present a generic approach to transform the fuzzy relational algebra into the fuzzy HBase manipulation language.