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To find the root causes and bridge the huge performance\/memory-footprint gap, we revisit the architectural features of two representative indexing mechanisms (single-stage and multi-stage) and propose a three-stage KVS called FluidKV. FluidKV effectively consolidates these indexes by fast and seamlessly running incoming key-value request stream from the write-concurrent frontend stage to the memory-efficient backend stage across an intermediate stage. FluidKV also designs important enabling techniques, such as thread-exclusive logging, PM-friendly KV-block structures, and dual-grained indexes, to fully utilize both parallel-processing and high-bandwidth capabilities of ultra-fast storage hardware while reducing the overhead. We implemented a FluidKV prototype and evaluated it under a variety of workloads. The results show that FluidKV outperforms the state-of-the-art PM-aware KVSs, including ListDB and FlatStore with different indexes, by up to 9\u00d7 and 3.9\u00d7 in write and read throughput respectively, while cutting up to 90% of the DRAM footprint.<\/jats:p>","DOI":"10.14778\/3648160.3648177","type":"journal-article","created":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T21:52:53Z","timestamp":1714773173000},"page":"1377-1390","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["FluidKV: Seamlessly Bridging the Gap between Indexing Performance and Memory-Footprint on Ultra-Fast Storage"],"prefix":"10.14778","volume":"17","author":[{"given":"Ziyi","family":"Lu","sequence":"first","affiliation":[{"name":"Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Cao","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Jiang","sequence":"additional","affiliation":[{"name":"UT Arlington, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxing","family":"Chen","sequence":"additional","affiliation":[{"name":"Tencent Inc., China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Yao","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anqun","family":"Pan","sequence":"additional","affiliation":[{"name":"Tencent Inc., China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,3]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Enabling CXL Memory Expansion for In-Memory Database Management Systems. 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