The article discusses the transformation of data management solutions in response to evolving business needs. It highlights how traditional relational databases, such as Oracle and MySQL, are struggling to cope with the increasing variety of data types including semi-structured and unstructured data. As businesses require real-time analytics and AI capabilities, the need for modern, flexible database solutions becomes more crucial. The first part of the series sets the stage for understanding these crucial changes in the data management landscape.
As part of our series, Database Revolution: A Modern Guide to Data Management, we explore how the database landscape is changing and why modern data management solutions are becoming indispensable.
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.
But 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 (such as images, videos, and IoT sensor data).
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