Making 768 servers look like 1

Scaling large-scale applications with millions of users and queries often requires sophisticated database infrastructure, and database sharding emerges as a crucial solution for handling vast data volumes and high query loads. Sharding involves distributing data and queries across multiple servers, allowing for more efficient management of resources and overcoming the bottlenecks of traditional single-node databases, such as write limitations and insufficient data capacity. The process involves sophisticated proxy layers, like Neki for Postgres and Vitess for MySQL, which act as middleware between application and database servers to ensure seamless query routing and data distribution across shards. These proxies maintain a cohesive view for the application, making numerous servers appear as a single database entity. The setup often includes multiple proxies and potentially network load balancers to handle traffic efficiently. Sharding is recommended for databases exceeding a few terabytes to avoid constraints like long backup times and write bottlenecks, with Neki and Vitess offering robust solutions for Postgres and MySQL respectively, supported by extensive operational expertise.

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