What are the storage methods of big data?

Big data storage methods include distributed storage and storage virtualization.

Distributed storage is a data storage mode with high fault tolerance, high throughput and batch processing, which is suitable for large-scale data analysis problems. Distributed file system stores and manages multiple files, and provides high-throughput data access through centralized storage and distributed file system. A distributed system is composed of several independent processing units, which cooperate to complete the specified tasks through the interconnection of computer networks.

Compared with traditional centralized storage, distributed storage system can provide higher flexibility, but the problems of data dispersion and data redundancy need to be considered. Storage virtualization is one of the big data storage solutions, which reduces idle and wasted storage space through thin provisioning and storage resource pool sharing.

The Significance of Big Data Storage

Big data has several meanings. IT can describe the scale of an organization, and more importantly, it defines the scale of IT infrastructure in an enterprise. The industry has placed infinite expectations on big data applications. The more business information accumulates, the greater the value, but we need a way to tap these values.

With the explosive growth of big data applications, it has derived its own unique architecture, which directly promoted the development of storage, network and computing technology. After all, dealing with the special needs of big data is a new challenge. The development of hardware is ultimately driven by software requirements. In this case, we can clearly see that the application demand of big data analysis is affecting the development of data storage infrastructure.