Enhancement of a Transformation Algorithm to Migrate SQL Database into NoSQL Graph Database

Abstract

With the proliferation of data, relational database management systems face the challenge of managing big volumes of data because of the absence of dynamic data models, high functioning, high scalability, high availability, and low cost. The NoSQL technology has the features which RDBMS lacks. Therefore, many organizations are migrating from RDBMS to NoSQL databases. The migration from RDBMS to NoSQL is not always effective if the data is lost, if the data is replicated while transmission, and if the performance is degraded. For this reason, enhancement of transformation algorithm proposed by Shabana Ramzan et al. has been performed to implement the methodology which is used to successfully migrate data from structured and normalized SQL database MySQL to NoSQL graph database Neo4j. SchemaCrawler engine has been used to metamodeling from source to destination database and execute the transformation rules. This study has also evaluated and validated the performance of the enhanced algorithm after successful migration of data. The NoSQL graph database Neo4j handles the most common form of data that are unstructured, semi-structured, and structured as well as they support the ACID property of relational databases. This feature is not supported by other NoSQL databases such as Oracle NoSQL, MongoDB, and HBase databases.

Keywords

• sql database
• nosql database
• mysql
• neo4j
• schemacrawler
• sitra