This article discusses the drastic shifts in data management driven by evolving business requirements. Traditional relational databases, like Oracle and SQL Server, have served well for structured data but struggle with the diverse data types prevalent in modern applications, including semi-structured and unstructured data. As businesses increasingly rely on real-time analytics and AI, the limitations of older database systems highlight the need for innovative data management solutions that can accommodate this variety and complexity.
For decades, relational databases such as Oracle, MySQL, and SQL Server have served as the backbone of data management. These systems are built to handle structured data within predefined schemas, excelling in transaction processing and analytical queries.
As data types evolve and application needs grow, traditional databases are falling short. Today's applications generate a broad range of data, from structured data to semi-structured (like JSON) and unstructured formats.
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