Implementation of GRAC algorithm (Graph Algorithm Clustering) in graph database compression
I Gusti Bagus Ady Sutrisna, W Kemas Rahmat Saleh, Alfian Akbar Gozali · 2015
Graph database is a representative of a data collection modeling into Node and Edge form. Graph database is one of implemented method of NoSQL (Not Only SQL), i.e. database system that is useful for data storage in a large number and is represented in the form of graph so that the data have high accessibility. However, the stored data in Graph database processing is not efficient yet in terms of data storage. The storage of million or billion nodes and edges requires compression. In this research, the conducted graph database compression uses GRAC (Graph Algorithm Clustering). The used Graph Database is the one which includes collaboration data among journal writers. In GRAC (Graph Algorithm Clustering), Hierarchical Clustering is used. It is a method that clusters Nodes into Cluster Nodes hierarchically. In the hierarchical cluster making, the strategy used is Agglomerative in which every node combined into a cluster. By applying GRAC (Graph Algorithm Clustering) using Hierarchical Clustering that forms hierarchical clusters, the lossless and well-compressed graph database will be resulted.