PRDCC: PRedictive Deterministic Concurrency Control under High Contention

Deterministic databases present a promising direction for building scalable OLTP systems by establishing a global transaction order prior to execution, thereby eliminating costly runtime coordination overhead. However, existing methods face significant limitations: the Ordering-Constrained protocols strictly commit transactions in a predetermined TID order, limiting concurrency and scalability; meanwhile, execution-order-independent approaches can incur substantial conflicts, cascading aborts, and retries under high-contention workloads. In this paper, we propose PRDCC, a prediction-driven framework for deterministic concurrency control, designed to mitigate abort-induced throughput collapse under high data contention. PRDCC combines (i) a deterministic conflict predictor for extractable point/range predicates that avoids physical pre-execution and provides a zero-false-negative guarantee within its supported predicate class, and (ii) a deterministic partitioning algorithm that uses predicted dependencies to form an ordered sequence of execution blocks. Experimental results show that PRDCC improves throughput by up to 4.1× over Aria on YCSB and 3.06× on TPC-C under high contention, while maintaining competitive performance in low-contention workloads.