Abstract
Modern applications produce and process massive amounts of activity (or log) data. Traditional storage systems were not designed with an append-only data model and a new storage abstraction aims to fill this gap: the distributed shared log store. However, existing solutions struggle to provide a scalable, parallel, and high-performance solution that can support a diverse set of conflicting log workload requirements. Finding the tail of a distributed log is a centralized point of contention. In this paper, we show how using physical time can help alleviate the need of centralized synchronization points. We present ChronoLog, a new, distributed, shared, and multi-tiered log store that can handle more than a million tail operations per second. Evaluation results show ChronoLog's potential, outperforming existing solution by an order of magnitude.