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Efficient in-memory data management

2014; Association for Computing Machinery; Volume: 7; Issue: 10 Linguagem: Inglês

10.14778/2732951.2732956

2150-8097

Hao Zhang, Bogdan Marius Tudor, Gang Chen, Beng Chin Ooi,

Advanced Data Storage Technologies

This paper analyzes the performance of three systems for in-memory data management: Memcached, Redis and the Resilient Distributed Datasets (RDD) implemented by Spark. By performing a thorough performance analysis of both analytics operations and fine-grained object operations such as set/get , we show that neither system handles efficiently both types of workloads. For Memcached and Redis the CPU and I/O performance of the TCP stack are the bottlenecks -- even when serving in-memory objects within a single server node. RDD does not support efficient get operation for random objects, due to a large startup cost of the get job. Our analysis reveals a set of features that a system must support in order to achieve efficient in-memory data management.