Comparison of search techniques in social graph neo4j

Abstract

Past few decades, relational databases was the dominant technology used in web and business applications where well structured data was widely used. In the era of BigData and social networking, data is in disorganized form. This unstructured data gives importance for relationships between entities and impersonate many-to-many relationships in graph database. This paper brings out the importance of graph NoSQL database Neo4j in social networks and further inquest how multilevel, multikeyword search in social graph Neo4j outperforms the search connected to relational databases. We summarize the current state of technologies existing in multilevel multikeyword search area, explore open issues as well as identify future directions for research in this important field of Big Data and social graphs in Neo4j. On the basis of comparative analysis, we found graph databases that the former retrieve the results at faster pace. Many multilevel or multikeyword search methods on Neo4j was analyzed based on four research questions on five dimensions, but none of them put forward a benchmark model in the integration of multilevel multikeyword search evaluation.