With the development of digital economy industry driven by IT technologies such as cloud computing

internet of things and artificial intelligence

modern enterprise information demands put forward higher requirements and challenges for data center storage capacity. Due to data storage reliability and redundant arrays of independent disks scalability

RAID system is widely used. In order to fulfill the requirements of massive data for the increasing storage capacity

the industry generally adopts a method of scaling RAID system to solve the problem of storing massive data. E-commerce

web service and finance access data on real-time

which make the data center must provide high-quality service response for users with 7*24

but the factors of data migration

load balane and scaling cost will affect the efficiency of RAID scaling. Therefore

how to design a fast and efficient scaling scheme is getting more and more attention from researchers. According to the different investigative object

this paper classifies RAID scaling approaches into basing on block

object and file system. Meanwhile

according to the investigative developing process and different optimization strategies of RAID scaling

the approaches also can divide into optimizing data migration process and reducing the number of data to be moved. From the perspective of evaluating the performance of the scaling schemes

this article introduces the typical and common scaling schemes by different application scenarios that points out the shortcomings of various scaling schemes and possible improvements. How to balance the factors that affect the performance of the scaling schemes and design a high-performance scaling scheme with less data migration

good load balance

and low scaling cost

which will be a hot issue for massive data storage research for a long time in the future.