An Efficient Index based Query handling model for Neo4j
Anita Brigit Mathew, S. D. Madhu Kumar · 2014
Relational Database Management Systems (RDMBS) are a predominant technology used for storing and retrieving structured data in web and business applications since 1980. However, relational databases have started losing its importance due to strict schema reliance and costly infrastructure. It has conjointly led to the problem in upgrade relationships between objects. Another important issue of failure is the brobdingnagian growth of BigData. A new database model called NoSQL, plays a vital role in BigData analytics. In this paper one of the NoSQL graph database's particularly Neo4j have been explored. Neo4j, is a reliable graph database which can be scalable to any application. It handles billions of nodes and relationships in a connected structure. Querying in Neo4j is administrated through graph traversals and aggregate operations. Another technique called Multidimenstional indexing was incorporated to speed up query process. Multidimenstional indexing search and insert algorithms have been analyzed and a new Skip list indexing is steered. Multiple skip lists with replication factor of three was incorporated that gave a Skip graph like structure. Analysis have been made and found that Skip list resulted in better performance compared to Multidimenstional indexing.