Segcache: a memory-efficient and scalable in-memory key-value cache for small objects


Juncheng Yang, Carnegie Mellon University; Yao Yue, Twitter; Rashmi Vinayak, Carnegie Mellon University

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Modern web applications heavily rely on in-memory key-value caches to deliver low-latency, high-throughput services. In-memory caches store small objects of size in the range of 10s to 1000s of bytes, and use TTLs widely for data freshness and implicit delete. Current solutions have relatively large per-object metadata and cannot remove expired objects promptly without incurring a high overhead. We present Segcache, which uses a segment-structured design that stores data in fixed-size segments with three key features: (1) it groups objects with similar creation and expiration time into the segments for efficient expiration and eviction, (2) it approximates some and lifts most per-object metadata into the shared segment header and shared information slot in the hash table for object metadata reduction, and (3) it performs segment-level bulk expiration and eviction with tiny critical sections for high scalability. Evaluation using production traces shows that Segcache uses 22-60% less memory than state-of-the-art designs for a variety of workloads. Segcache simultaneously delivers high throughput, up to 40% better than Memcached on a single thread. It exhibits close-to-linear scalability, providing a close to 8× speedup over Memcached with 24 threads.

NSDI '21 Open Access Sponsored by NetApp

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@inproceedings {265055,
author = {Juncheng Yang and Yao Yue and Rashmi Vinayak},
title = {Segcache: a memory-efficient and scalable in-memory key-value cache for small objects},
booktitle = {18th USENIX Symposium on Networked Systems Design and Implementation (NSDI 21)},
year = {2021},
isbn = {978-1-939133-21-2},
pages = {503--518},
url = {},
publisher = {USENIX Association},
month = apr

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