In view of the practical application problems of the traditional parallel processing technology existing in the processing of the massive data, using the powerful cloud computing power and the efficient massive data processing method, combined with the advantages of the real-time access of the relational database, based on the Hadoop distributed computing framework, using the Map-Reduce framework, the author designs and implements the massive data processing platform based on the cloud computing. Practice has proved that the system is superior to the traditional parallel processing technology in the computing power, the stability, the scalability and other aspects, and can effectively solve the large concurrent access of the massive data. In many industries and institutions, the rapid batch processing of the large data sets of the large and medium-sized databases and data warehouses has the wide range of the application requirements. How to realize the fast and interactive batch processing of the massive data is an increasingly prominent problem in the management information system, and it is also the key problem to be solved in the engineering of the data sets. The traditional data platform based on the parallel processing has been unable to meet the actual requirements of the massive data processing, and the architecture of the massive information technology urgently needs the dynamic and scalable storage and calculation model, in order to achieve the rapid response mechanism. In the large-scale database, the data query, analysis, extraction, updating and other batch processing processes are facing the serious practical problems. First, the traditional database is complex, and the query time is too long. When we are faced with a query task with the large amount of the data, it even cannot complete it. Second, when the system is faced with the data task of the concurrency, the performance of the system will be drastically reduced. Third, the expandability of the traditional database is poor, and the additionally expandable hardware cannot effectively improve the performances of the system processing. Fourth, the cost of the massive data retrieval and processing is high, with the high maintenance cost. In the researches on the massive data, the processing technology in time with the high efficiency will effectively improve the application performances of the computer system, so as to provide the better social basic services, and promote the growth of the economic efficiency. As a new business computing model based on the Internet, the cloud computing provides the flexible computing capability and the efficient method for processing the massive data. The author of this paper applies the cloud computing to the massive data processing of the relational database, and designs and builds the massive data processing platform based on the cloud computing, and provides a new method for the solution to the processing of the massive data in the relational database.