Distributed Database Using Sharding Database Architecture

Distributed Database Using Sharding Database Architecture

연구 분야: Databases

학회: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)

This article aims at introducing distributed databases that are becoming increasingly popular. In the distributed database system, we implement sharding for the distribution of vertical and horizontal fragmentation. In today's business environment there is a growing need for distributed databases and client/server applications as the demand for reliable, scalable and accessible information continues to grow. Distributed database systems provide improvements in communication and data processing due to the distribution of its data across different network sites. Not only is data access faster, but a point of failure is also less likely, and it gives users local control over the data. Some concerns are being addressed when designing and using these strategies. A distributed database is a collection of databases that can be stored on various computer network sites. This article gives an overview of the advantages and disadvantages as well as distributed database systems. This article also covers various aspects such as duplication, fragmentation and various issues that can be encountered in a distributed database system. Fragmenting data involves optimization because each query involves adding more than one piece of data to different sites. It produces a high time response. The scientific approach to solving this problem has been tested because it is known as the non-deterministic polynomial-time hard problem. Extracting data is another special issue that involves finding the maximum distribution of fragments on sites. This non-multiple polynomial has already proven to be a complete problem. In this article, we have to implement the distribution of the database through the process of acceleration.