Abstract—As a traditional relational database, MySQL provides complete ACID operations, supports rich data types, powerful associated queries, where statements, etc., can easily establish query indexes, perform complex operations such as internal connection, external connection, summation, sorting, grouping, and support functions such as stored procedures. The product is highly mature and powerful. However, when databases face large-scale data access, disk I/O often becomes a performance bottleneck. In complex telecommunications business scenarios, high-frequency access to data such as product instances, sales product instances, product/sales product specifications, and accounts in telecommunications business can result in high database load and low efficiency if operated directly across tables or databases. Adopting distributed caching products can greatly improve performance and reduce database load. Therefore, this article proposes a distributed caching system to solve the disk I/O performance bottleneck caused by large-scale and high concurrency database access. It is a memory based, persistence, high-performance, highly reliable, and horizontally scalable distributed NoSQL memory database product. It supports memory management of sub databases and sub tables, provides disaster recovery, recovery, monitoring, migration and other capabilities, and supports transparent access for API provisioning.

Keywords—database, distributed, massive scale, high concurrency

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Cite: Lanying Shi, Hongming Qiao, Chengwei Yang, Yiquan Jiang, Kefeng Yu, Chunhua Chen , "Research and Application of Distributed Cache Based on Redis," Journal of Software vol. 19, no. 1, pp. 1-8, 2024.

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