Abstract: As RDF(Resource Description Framework) is flexible to express and easy to interchange, the volume of RDF data is increasing rapidly. TripleBit aims to propose an efficient approach in data storage and query processing for large scale RDF data in several aspects. TripleBit employs delta compression and variable integer encoding schemes in order to reduce the storage space. The data tables are partitioned into several chunks, which not only facilitate the buffer management but also make the data more compact, therefore it can accelerate the query processing. We employ heuristic rules to generate query plan dynamically. Besides, two-stage execution strategy is used in multiple-variable query which can reduce the intermediate result. The performance evaluation is compared with the state of art RDF stores, such as RDF-3X, MonetDB. Experimental results demonstrate that TripleBit saves at least 40% storage space while the speed of query processing has been improved very much.