Why concurrency control matters: In which situation is concurrency control primarily needed to preserve data integrity?

Introduction / Context:
Concurrency control coordinates simultaneous operations on shared data. Without it, overlapping updates can cause lost updates, dirty reads, non-repeatable reads, and other anomalies that compromise correctness in multiuser systems.

Given Data / Assumptions:

• Multiple users or processes may modify the same data concurrently.
• Transactions bundle operations to maintain ACID properties.
• Isolation and locking/serialization strategies are available.

Concept / Approach:

The greatest integrity risk arises when two or more sessions perform updates at the same time. Concurrency control (locks, MVCC, optimistic control) ensures that the outcome is equivalent to some serial order of transactions, preserving consistency. Read-only workloads do require isolation guarantees for correct semantics, but integrity hazards are most acute with concurrent writes.

Step-by-Step Solution:

Verification / Alternative check:

Simulate two update transactions on the same row without control; observe conflicts and inconsistencies. Enable proper isolation; results become deterministic and correct.

Why Other Options Are Wrong:

Single-user environments have no concurrent writers; concurrency control is unnecessary.

Reads in multiuser environments matter for semantics, but the question asks about preserving data integrity, which is primarily threatened by concurrent updates.

Single-user reads pose no concurrency threat.

Common Pitfalls:

Using overly weak isolation for write-heavy workloads; ignoring phantom anomalies; misconfiguring lock timeouts causing deadlocks and rollbacks.

Final Answer:

To ensure data integrity when updates occur to the database in a multiuser environment