Optimistic vs Pessimistic Concurrency in SQL Server

Suppose we are booking a room on the hotel and there is only 1 room available. Customer A opens booking page. Hotel immediately reserves the room. Room 101 Locked Customer B tries to book Please Wait Room Currently Reserved Customer B must wait. This is exactly how SQL Server locks work. This is Pessimistic Concurrency.

Customer A opens booking page. Customer B also opens booking page. Both seen Room Available. No lock is taken. When Customer A confirms booking success. When Customer B confirms booking Sorry, room already booked. Conflict detected later. This is Optimistic Concurrency.

SQL Server Mapping

Concurrency Model	SQL Server Feature
Pessimistic	READ COMMITTED
Pessimistic	REPEATABLE READ
Pessimistic	SERIALIZABLE
Optimistic	SNAPSHOT
Optimistic	RCSI (Read Committed Snapshot Isolation)

Comparison Table

Feature	Pessimistic Concurrency	Optimistic Concurrency
Assumption	Conflicts are common	Conflicts are rare
Uses Locks	Yes	Minimal
Blocking	High	Low
Deadlocks	Possible	Rare
Concurrency	Lower	Higher
TempDB Usage	No	Yes
Update Conflict	No	Yes (3960)
Reader-Writer Blocking	Yes	No
Performance	Lower	Higher
Best For	OLTP with frequent updates	Reporting, High-Concurrency Systems

Pessimistic Concurrency assumes that data conflicts are likely, so SQL Server acquires locks before reading or modifying data. This prevents other transactions from making conflicting changes but can cause blocking and deadlocks. Isolation levels such as READ COMMITTED, REPEATABLE READ, and SERIALIZABLE use pessimistic concurrency. Optimistic Concurrency assumes conflicts are rare. Instead of locking rows for reads, SQL Server uses row versioning stored in TempDB. Transactions work on snapshots of data and conflicts are checked when updates occur. SNAPSHOT Isolation and RCSI are examples of optimistic concurrency. If another transaction changes a row after the snapshot transaction begins, SQL Server raises error 3960 and aborts the transaction. Pessimistic concurrency provides stronger immediate protection but lower concurrency, while optimistic concurrency provides higher scalability and lower blocking at the cost of possible update conflicts and additional TempDB usage.