Abstract: Graph is an important data model, which can describe structural information including dependent relationship, such as transportation network, social network and webpage hyperlink. Management of big graph brings challenges for traditional techniques, however, distributed cluster provide platform and techniques for this problem. Nowadays, the ratio of performance and price of memory promote rapidly, while demand of applications of highperformance, inmemory computing for massive data management is becoming popular. The storage and evaluation of massive graph requires highperformance platform. In this context, it’s significant for studying graph data management with inmemory techniques. This paper surveyes key techniques of management of massive graph data, and researched graph data management of inmemory computing techniques，and finally summarizes the paper.