Semi-Automated Strategy for Efficient Migration from SQL to NoSQL

Abstract

As more applications are migrated to NoSQL databases, they often rely on general guidelines to select appropriate schemas, but these methods do not fully address the unique challenges posed by NoSQL systems. Traditional relational database schema optimization techniques are not directly applicable to NoSQL environments, leading to inefficiencies in schema design. This paper introduces an approach for designing optimal database schemas specifically tailored for NoSQL databases like MongoDB. We propose a semi-automated schema model to recommend schemas and query plans based on Metadata SQL query information. The model captures Meta data information of SQL database and used as a suggestive measure to design NoSQL database. The key parameters captured are primary key, foreign key, table size and cardinality. The decision is made based on these parameters and manual interventions of frequently executed SQL queries indicating joins. This approach aims to simplify the development process, enhance database performance and scalability through our proposed model. To evaluate the impact of proposed model three benchmark workloads were implemented using the Yahoo! Cloud Serving Benchmark (YCSB) framework, especially focused on eliminating joins.