Distributed databases: Is concurrency control generally more complex in a distributed database environment than in a centralized database?

Introduction / Context:
Concurrency control ensures correctness under concurrent access. Distributed databases add network partitions, message delays, and cross-site failures to the equation. This question evaluates whether distribution inherently complicates concurrency management.

Given Data / Assumptions:

• Multiple nodes participate in transactions and queries.
• Links can fail or degrade; clocks may not be perfectly synchronized.
• Consistency requirements (from eventual to strong) vary by system and workload.

Concept / Approach:
Compared to a single-node database, a distributed system must coordinate locks or validations across sites, manage deadlock detection across networks, and ensure atomic commit (often via two-phase commit). Latency and partial failures complicate both pessimistic (locking) and optimistic (timestamp/MVCC) approaches. Replication (synchronous or asynchronous) introduces further ordering and conflict resolution challenges.

Step-by-Step Solution:

Verification / Alternative check:
Measure abort rates and lock wait graphs under cross-site load; expect higher complexity and overhead than on a centralized node due to coordination costs and failures.

Why Other Options Are Wrong:

• “Incorrect because each node controls its own locks” ignores global conflicts in cross-site transactions.
• Restricting complexity to synchronous replication or read-write only is too narrow; distributed reads can also face staleness and ordering concerns.

Common Pitfalls:
Underestimating network impact, neglecting idempotency, or failing to design for partitions and retries. Choose consistency levels and transaction scope intentionally.

Final Answer:
Correct