Distributed databases leverage distributed computing principles to store data across multiple servers, forming clusters that function as a single database entity. Unlike traditional single server databases, distributed databases offer horizontal scaling, high availability, and replication, which are crucial for handling increased loads and ensuring data accessibility even if one server fails. Key architectures include the primary/secondary model, where a primary server manages data and updates secondary servers, and the shared-nothing model, which partitions data into shards distributed across nodes to balance load and maintain availability. Notably, NoSQL databases such as Couchbase and MongoDB utilize distinctive sharding techniques; Couchbase automates sharding using a fixed number of vBuckets and a CRC32 hashing algorithm, while MongoDB requires manual shard key selection and employs a query router and config server to manage data distribution. These systems enable scalable data management and efficient resource utilization, with each method offering unique advantages and demanding different levels of user involvement in configuration and maintenance.