Temporal Consistency Models for Financial Data Processing in Distributed Systems

Abstract

For most distributed financial systems, the constraints imposed by the CAP (Consistency, Availability, Partition Tolerance) theorem must be reconciled against the ordering constraints needed to satisfy regulatory requirements and meet the performance requirements of real-time transaction processing. This paper presents the Temporal Sequence Barrier consistency model for asynchronous high-throughput ledger systems. Combining logical vector clocks with epoch-based orchestration patterns imposes a strict causal ordering of events across multiple geographic regions without sacrificing availability. Its database-centric architecture allows stateful routing and selective replication of entities in order to achieve linearizability of causally related transactions while allowing independent sets of entities to be processed in parallel. We provide a detailed evaluation that shows that we can provide causal consistency at latency bounds equal to or better than existing systems using clever buffering and adaptive timeouts, while also addressing the classic challenges in distributed transaction management and operator complexity.