The gradual popularization of IoT devices, increasing data analysis, and application cloudification have driven a massive increase in stored data. According to analysis, the global data volume will reach 180ZB in 2025. Although enterprises are aware of the huge value contained in data, and big data analysis has become a new engine for enterprise development, many data have not been activated or utilized, and a large amount of data value has been lost. According to IDC's "New Horizons in Data" report, only 32 percent of the data that businesses generate in their operations is utilized. Unstructured data contains a lot of information. Unstructured data accounts for 80% of the data generated by enterprises, and it is rapidly expanding at a compound annual growth rate of 60%. How to manage massive unstructured data and tap its value, It has become a problem that plagues enterprise data management.
Files and objects are two ways to organize unstructured data. Files adopt a hierarchical structure, which is more in line with human logic. Files can be frequently edited and modified, which is suitable for scenarios such as file sharing, video editing, and high-performance analysis. The object is a flat architecture, which is more machine-friendly and rarely modified. It is suitable for scenarios such as cloud-native applications, cloud resource pools, and content publishing. However, the scenarios of files and objects are not fixed. Most applications based on file storage can be converted to object storage after adaptation and transformation. In addition, for scenarios such as backup and archiving, big data analysis, etc., either the file method or the object method can be used. Therefore, enterprises also need cross-protocol data flow capabilities to manage unstructured data in a unified manner and arrange resources reasonably.
