In-memory key-value stores have quickly become a key enabling technology to build high-performance applications that must cope with massively distributed workloads. In-memory key-value stores (also referred to as NoSQL) primarly aim to offer low-latency and high-throughput data access which motivates the rapid adoption of modern network cards such as Remote Direct Memory Access (RDMA). In this paper, we present the fundamental design principles for exploiting RDMAs in modern NoSQL systems. Moreover, we describe a break-down analysis of the state-of-the-art of the RDMA-based in-memory NoSQL systems regarding the indexing, data consistency, and the communication protocol. In addition, we compare traditional in-memory NoSQL with their RDMA-enabled counterparts. Finally, we present a comprehensive analysis and evaluation of the existing systems according to the impact of the number of clients, real-world request distributions, and workload read-write ratios.

Analyzing In-Memory NoSQL Landscape / Hemmatpour, Masoud; Montrucchio, Bartolomeo; Rebaudengo, Maurizio; Sadoghi, Mohammad. - In: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. - ISSN 1041-4347. - ELETTRONICO. - 34:4(2020), pp. 1628-1643. [10.1109/TKDE.2020.3002908]

Analyzing In-Memory NoSQL Landscape

Hemmatpour, Masoud;Montrucchio, Bartolomeo;Rebaudengo, Maurizio;
2020

Abstract

In-memory key-value stores have quickly become a key enabling technology to build high-performance applications that must cope with massively distributed workloads. In-memory key-value stores (also referred to as NoSQL) primarly aim to offer low-latency and high-throughput data access which motivates the rapid adoption of modern network cards such as Remote Direct Memory Access (RDMA). In this paper, we present the fundamental design principles for exploiting RDMAs in modern NoSQL systems. Moreover, we describe a break-down analysis of the state-of-the-art of the RDMA-based in-memory NoSQL systems regarding the indexing, data consistency, and the communication protocol. In addition, we compare traditional in-memory NoSQL with their RDMA-enabled counterparts. Finally, we present a comprehensive analysis and evaluation of the existing systems according to the impact of the number of clients, real-world request distributions, and workload read-write ratios.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2856352