Businesses are increasingly adopting modern data management solutions as traditional databases fail to meet new demands. With diverse data types and the need for real-time processing, these conventional systems struggle, leading to limitations in scalability and adaptation to cloud-native architectures. As the quantity of generated data is projected to soar to 175 zettabytes by 2025, organizations face the challenge of choosing systems capable of robustly managing both structured and unstructured data across varied environments. This shift signifies a pivotal change in how data is orchestrated for analytics and operational use.
The push for modern database solutions is driven by the explosive growth of data, targeting the evolving needs of businesses in a data-driven environment.
Traditional databases struggle with diverse data types and real-time processing, prompting businesses to seek modern solutions capable of managing various data forms.
By 2025, global data creation is expected to reach 175 zettabytes, highlighting the critical need for advanced data management systems that can handle such scale.
Cloud-native architectures are now the standard, but traditional databases often fail to adapt to these environments, limiting their utility in modern applications.
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