Concurrency Control, Locking, Timestamping, and Deadlocks
Study the mechanisms a DBMS uses to coordinate simultaneous access safely without destroying performance or correctness.
Inside this chapter
- Why Concurrency Control Exists
- Lock-Based Protocols
- Timestamp Ordering
- Deadlocks
- Isolation Levels
- Operational Example
Series navigation
Study the chapters in order for the clearest path from database fundamentals and SQL to transactions, indexing, recovery, distributed systems, tuning, and advanced DBMS engineering understanding. Use the navigation at the bottom to move smoothly across the full tutorial series.
Why Concurrency Control Exists
Modern databases are multi-user systems. At any moment, many transactions may read and write the same data. Concurrency control ensures correct outcomes while still allowing useful parallelism.
Lock-Based Protocols
Locks can be shared for reads or exclusive for writes. Two-phase locking is a classic protocol used to achieve serializable schedules by controlling when locks are acquired and released.
Timestamp Ordering
In timestamp-based methods, transactions are ordered logically by timestamps, and operations are allowed or rejected based on that order. This avoids certain lock conflicts but introduces other tradeoffs.
Deadlocks
A deadlock occurs when transactions wait on each other in a cycle. Databases may detect, prevent, or resolve deadlocks by aborting one participant and rolling it back.
T1 holds row A and waits for row B
T2 holds row B and waits for row AIsolation Levels
Many DBMS products expose isolation levels such as Read Uncommitted, Read Committed, Repeatable Read, and Serializable. Higher isolation gives stronger guarantees but can reduce concurrency and throughput.
Operational Example
An inventory system during a festival sale may receive huge concurrent order traffic. Concurrency control is what ensures stock counts do not become incorrect under heavy simultaneous access.