How Databases Handle Thousands of Concurrent Users: A Technical Deep Dive

Modern relational databases like PostgreSQL and MySQL use several concurrency control strategies to maintain data integrity when thousands of users access them simultaneously. Pessimistic concurrency relies on locking mechanisms such as Two-Phase Locking, while optimistic concurrency skips locks and instead validates data versions at commit time, making it better suited for read-heavy workloads. Multi-Version Concurrency Control (MVCC) is the widely preferred approach, creating new row versions on each update so readers and writers never block each other. Databases also use a RAM-based Buffer Pool to avoid slow disk reads, with lightweight latches protecting in-memory structures at the CPU instruction level. Background processes like PostgreSQL's Vacuum clean up obsolete row versions created by MVCC to prevent storage bloat.