Modern NVMe solid state drives offer significantly higher bandwidth and low latency than prior storage devices. Current key-value stores struggle to fully utilize the bandwidth of such devices. This paper presents SplinterDB, a new key-value store explicitly designed for NVMe solid state drives. SplinterDB is designed around a novel data structure (the STBε-tree), that exposes I/O and CPU concurrency and reduces write amplification without sacrificing query performance. STBε-tree combines ideas from log-structured merge trees and Bε-trees to reduce write amplification and CPU costs of compaction. The SplinterDB memtable and cache are designed to be highly concurrent and to reduce cache misses. We evaluate SplinterDB on a number of micro- and macro-benchmarks, and show that SplinterDB outperforms RocksDB, a state-of-the-art key-value store, by a factor of 6–10x on insertions and 2–2.6x on point queries, while matching RocksDB on small range queries. Furthermore, SplinterDB reduces write amplification by 2x compared to RocksDB.
SplinterDB: Closing the Bandwidth Gap for NVMe Key-Value Stores
Modern NVMe solid state drives offer significantly higher bandwidth and low latency than prior storage devices. Current key-value stores struggle to fully utilize the bandwidth of such devices. This paper presents SplinterDB, a new key-value store explicitly designed for NVMe solid state drives.
SplinterDB is designed around a novel data structure (the STBε-tree), that exposes I/O and CPU concurrency and reduces write amplification without sacrificing query performance. STBε-tree combines ideas from log-structured merge trees and Bε-trees to reduce write amplification and CPU costs of compaction. The SplinterDB memtable and cache are designed to be highly concurrent and to reduce cache misses.
We evaluate SplinterDB on a number of micro- and macro-benchmarks, and show that SplinterDB outperforms RocksDB, a state-of-the-art key-value store, by a factor of 6–10x on insertions and 2–2.6x on point queries, while matching RocksDB on small range queries. Furthermore, SplinterDB reduces write amplification by 2x compared to RocksDB.
- Award ID(s):
- 1751277
- Publication Date:
- NSF-PAR ID:
- 10180595
- Journal Name:
- 2020 USENIX Annual Technical Conference
- Sponsoring Org:
- National Science Foundation
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Modern NVMe solid state drives offer significantly higher bandwidth and lower latency than prior storage devices. Cur- rent key-value stores struggle to fully utilize the bandwidth of such devices. This paper presents SplinterDB, a new key- value store explicitly designed for NVMe solid-state-drives. SplinterDB is designed around a novel data structure (the STBe-tree) that exposes I/O and CPU concurrency and re- duces write amplification without sacrificing query perfor- mance. STBe-tree combines ideas from log-structured merge trees and Be-trees to reduce write amplification and CPU costs of compaction. The SplinterDB memtable and cache are designed to be highly concurrent and to reduce cache misses. We evaluate SplinterDB on a number of micro- and macro-benchmarks, and show that SplinterDB outperforms RocksDB, a state-of-the-art key-value store, by a factor of 6–10⇥ on insertions and 2–2.6⇥ on point queries, while matching RocksDB on small range queries. Furthermore, SplinterDB reduces write amplification by 2⇥ compared to RocksDB.
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