Challenges and solutions for distributed data management
When we talk about large-scale web applications, we have to consider the storage backends to scale and support concurrency.
Through scalability, we aim for incredible data capabilities and very high read/write speeds. The model application server processes a huge number of applications at the same time. Since they rely on background storage systems, they also face very concurrent access at this level.
Performance and capacity expansion can only be achieved sustainably through the horizontal scale mechanism. Even with special hardware equipment, a single database server can only be scaled to a specific load. As a result, we need a parallel distributed system for scalable backend storage.
Background storage needs to maintain the status of an application, so we also expect some consistency of data when reading/writing data into it.
Generally, in distributed systems, failures are often to be expected in advance. If a...
