TY - GEN
T1 - FlashKey:A High-Performance Flash Friendly Key-Value Store
AU - Ray, Madhurima
AU - Kant, Krishna
AU - Li, Peng
AU - Trika, Sanjeev
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Key-value stores (KVS) provide an efficient storage for increasing amounts of semi-structured or unstructured data generated by many applications. Most KVS in existence have been designed for hard-disk based storage where avoiding random accesses is crucial for good performance. Unfortunately, the resulting storage structures result in high read, write, and space amplifications when used on modern SSDs. In this paper, we introduce a KV store especially designed for SSDs, called FlashKey, and demonstrate that even as an initial implementation, it substantially outperforms the two most popular commercial KVS in existence, namely, Google's LevelDB and Facebook's RocksDB. In particular, we show that FlashKey achieves up to 85% improvement in average access latency, 2x improvement in tail latencies, and 12x improvement in write amplification, at comparable or better space-amplification. Furthermore, FlashKey can easily trade off space and write amplifications, thereby providing a new tuning knob that is difficult to implement in LevelDB and RocksDB.
AB - Key-value stores (KVS) provide an efficient storage for increasing amounts of semi-structured or unstructured data generated by many applications. Most KVS in existence have been designed for hard-disk based storage where avoiding random accesses is crucial for good performance. Unfortunately, the resulting storage structures result in high read, write, and space amplifications when used on modern SSDs. In this paper, we introduce a KV store especially designed for SSDs, called FlashKey, and demonstrate that even as an initial implementation, it substantially outperforms the two most popular commercial KVS in existence, namely, Google's LevelDB and Facebook's RocksDB. In particular, we show that FlashKey achieves up to 85% improvement in average access latency, 2x improvement in tail latencies, and 12x improvement in write amplification, at comparable or better space-amplification. Furthermore, FlashKey can easily trade off space and write amplifications, thereby providing a new tuning knob that is difficult to implement in LevelDB and RocksDB.
UR - http://www.scopus.com/inward/record.url?scp=85088892387&partnerID=8YFLogxK
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U2 - 10.1109/IPDPS47924.2020.00104
DO - 10.1109/IPDPS47924.2020.00104
M3 - Conference contribution
AN - SCOPUS:85088892387
T3 - Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020
SP - 976
EP - 985
BT - Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2020
Y2 - 18 May 2020 through 22 May 2020
ER -