From FASTER to F2: Evolving Concurrent Key-Value Store Designs for Large Skewed Workloads
Konstantinos Kanellis, Badrish Chandramouli, Ted Hart, Shivaram Venkataraman

TL;DR
F2, an evolution of the FASTER key-value store, introduces a two-tier design and new concurrency mechanisms to efficiently handle large, skewed workloads on modern hardware, significantly improving throughput.
Contribution
The paper presents F2, a novel KV store design with a two-tier architecture and latch-free algorithms, optimized for large skewed workloads, surpassing existing solutions in performance.
Findings
F2 achieves 2-11.9x higher throughput than existing KV stores.
F2 effectively manages large skewed workloads with reduced overhead.
The system is open-source and ready for deployment.
Abstract
Modern large-scale services such as search engines, messaging platforms, and serverless functions, rely on key-value (KV) stores to maintain high performance at scale. When such services are deployed in constrained memory environments, they present challenging requirements: point operations requiring high throughput, working sets much larger than main memory, and natural skew in key access patterns. Traditional KV stores, based on LSM- and B-Trees, have been widely used to handle such use cases, but they often suffer from suboptimal use of modern hardware resources. The FASTER project, developed as a high-performance open-source KV storage library, has demonstrated remarkable success in both in-memory and hybrid storage environments. However, when tasked with serving large skewed workloads, it faced challenges, including high indexing and compactions overheads, and inefficient…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Parallel Computing and Optimization Techniques · Cloud Computing and Resource Management
