Open Access

Arthur BernhardtORCiD, Sajjad TamimiORCiD, Florian StockORCiD, Andreas KochORCiD, Ilia PetrovORCiD

• The performance and scalability of modern data-intensive systems processing large datasets are limited by unnecessary data movement. Even though near-data processing (NDP) can provably reduce data transfers and increase performance, at present, NDP is utilized primarily in read-only settings. Near-data execution of data-intensive modification operations is currently infeasible due to the lack of transactional consistency and the absence of practicable low-latency synchronization mechanisms between the host database engine and the NDP-engine on smart storage. In this paper, we introduce Update NDP as an approach to offloading modifications to computational storage with transactional guarantees in an NDP database system called neoDBMS. To ensure consistency, we introduce a low-latency shared lock table between the host and computational storage, based on novel cache-coherent interconnects. We also introduce a novel locking protocol that seamlessly integrates the shared lock table within the lock manager of the host NDP-engine. To handle failure recovery, while preserving high and robust performance, we introduce novel extended locking and logging mechanisms that allow the host and computational storage to perform useful work during log-movement. Our evaluation indicates that in-storage modifications in neoDBMS in mixed workload settings are ≥ 6.52 × faster than host-only executions and exhibit robust performance due to lower data movement and better resource utilization.