Abstract
As data volumes grow exponentially, managing and storing this information efficiently becomes increasingly critical. NoSQL databases have emerged as a preferred solution for handling unstructured data, outperforming traditional relational database management systems (RDBMS) in scalability and flexibility. Techniques such as deduplication (removing duplicate data) and compression, combined with powerful tools like Hadoop and MongoDB, facilitate optimized storage and reduced network usage. However, the challenge of schema evolution in both NoSQL and SQL systems introduces risks of downtime and data inconsistency. This paper reviews current methods, highlights gaps in existing solutions, and proposes an integrated approach to ensure efficient data management across diverse database environments while minimizing downtime and enhancing data integrity.
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