Over the last decade, there has been a tremendous growth in data-intensive applications and services in the cloud. Data is created on a variety of edge sources, e.g., devices, browsers, and servers, and processed by cloud applications to gain insights or take decisions. Applications and services either work on collected data, or monitor and process data in real time. These applications are typically update intensive and involve a large amount of state beyond what can fit in main memory. However, they display significant temporal locality in their access pattern.
FASTER is a new key-value store for point operations, that combines a highly cache-optimized concurrent hash index with a novel self-tuning data organization. It extends the standard key-value store interface to handle read-modify-writes and blind update operations. FASTER achieves orders-of-magnitude better throughput – up to 160M operations per second on a single machine – than alternative systems deployed widely today, and exceeds the performance of pure in-memory data structures when the working set fits in memory.
NEWS: The FASTER research paper will appear at the SIGMOD 2018 conference. See below for a link to the paper.