Graphs increasingly stand out as an essential data structure in the field of data sciences. To study graphs, or sub-graphs, that char- acterize a set of observations, it is necessary to describe them formally, in order to characterize equivalence relations that make sense in the scope of the considered application domain. Hence we seek to define a canonical graph notation, so that two isomorphic (sub) graphs have the same canonical form. Such notation could subsequently be used to index and retrieve graphs or to embed them efficiently in some metric space. Sequential optimized algorithms solving this problem exist, but do not deal with labeled edges, a situation that occurs in important application domains such as chemistry. We present in this article a new algorithm based on graph rewriting that provides a general and complete solution to the graph canonization problem. Although not reported here, the formal proof of the validity of our algorithm has been established. This claim is clearly supported empirically by our experimentation on synthetic com- binatorics as well as natural graphs. Furthermore, our algorithm supports distributed implementations, leading to efficient computing perspectives.