Sharding is a database architecture technique that involves horizontally partitioning a large dataset into smaller, independent shards, each stored on different nodes, enabling horizontal scaling and improving query performance by directing operations to specific shards. This technique enhances reliability by isolating faults and is cost-effective as it allows the use of multiple commodity servers rather than a single expensive one. Despite its benefits, sharding introduces challenges such as implementation complexity, potential data hotspots, and the difficulty of reconfiguring a sharded database. It demands careful planning in selecting shard keys and strategies to avoid uneven data distribution. Advanced databases like Aerospike offer built-in sharding capabilities, automating many of these processes and mitigating common issues, thus providing a scalable and efficient solution for applications handling large-scale data and high traffic.