LavaStore: ByteDance's Purpose-built, High-performance, Cost-effective Local Storage Engine for Cloud Services

Summary: LavaStore tailors RocksDB for ByteDance’s write-heavy, cost- and tail-latency-sensitive workloads with KV separation, WAL specialization, and a user-space append-only filesystem. Deployed at >100 PB scale, it improves throughput, latency, and cost. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: h413b1863ef586a5d
Venue: VLDB
Year: 2024
Pagerank: 5.0925155e-05
Overall Rank: 10,029 | 32.58%
DOI: 10.14778/3685800.3685807

Incoming Non-self Citations Over Time

Authors

1. Hao Wang (ByteDance)
2. Jiaxin Ou (ByteDance)
3. Ming Zhao (ByteDance)
4. Sheng Qiu (ByteDance)
5. Yizheng Jiao (ByteDance)
6. Yi Wang (ByteDance)
7. Qizhong Mao (ByteDance)
8. Zhengyu Yang (ByteDance)
9. Yang Liu (ByteDance)
10. Jianshun Zhang (ByteDance)
11. Jianyang Hu (ByteDance)
12. Jingwei Zhang (ByteDance)
13. Jinrui Liu (ByteDance)
14. Jiaqiang Chen (ByteDance)
15. Yong Shen (ByteDance)
16. Lixun Cao (ByteDance)
17. Heng Zhang (ByteDance)
18. Hongde Li (ByteDance)
19. Ming Li (ByteDance)
20. Yue Ma (ByteDance)
21. Lei Zhang (ByteDance)
22. Jian Liu (ByteDance)
23. Guanghui Zhang (ByteDance)
24. Fei Liu (ByteDance)
25. Jianjun Chen (ByteDance)

BibTeX Citation

@article{wang_vldb24,
        title = {{LavaStore: ByteDance's Purpose-built, High-performance, Cost-effective Local Storage Engine for Cloud Services}},
        author = {Wang, Hao and Ou, Jiaxin and Zhao, Ming and Qiu, Sheng and Jiao, Yizheng and Wang, Yi and Mao, Qizhong and Yang, Zhengyu and Liu, Yang and Zhang, Jianshun and Hu, Jianyang and Zhang, Jingwei and Liu, Jinrui and Chen, Jiaqiang and Shen, Yong and Cao, Lixun and Zhang, Heng and Li, Hongde and Li, Ming and Ma, Yue and Zhang, Lei and Liu, Jian and Zhang, Guanghui and Liu, Fei and Chen, Jianjun},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {12},
        pages = {3799--3812},
        doi = {10.14778/3685800.3685807},
        url = {https://doi.org/10.14778/3685800.3685807},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,908	ABase: the Multi-Tenant NoSQL Serverless Database for Diverse and Dynamic Workloads in Large-scale Cloud Environments	2025	SIGMOD	5.1103839e-05
10,758	Dynamic read & write optimization with TurtleKV	2026	VLDB	4.9793485e-05
11,063	Terark-DS: A High-Performance and Storage-Efficient Key-Value Separation Storage Engine on Disaggregated Storage	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
400	Monkey: Optimal Navigable Key-Value Store	2017	SIGMOD	0.00019129175
754	Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging	2018	SIGMOD	0.00014236015
816	SlimDB: A Space-Efficient Key-Value Storage Engine For Semi-Sorted Data	2017	VLDB	0.00013687311
864	Let’s Talk About Storage & Recovery Methods for Non-Volatile Memory Database Systems	2015	SIGMOD	0.00013391824
891	SuRF: Practical Range Query Filtering with Fast Succinct Tries	2018	SIGMOD	0.00013245926
907	HOT: A Height Optimized Trie Index for Main-Memory Database Systems	2018	SIGMOD	0.00013158824
1,980	Chucky: A Succinct Cuckoo Filter for LSM-Tree	2021	SIGMOD	9.2595896e-05
2,510	Viper: An Efficient Hybrid PMem-DRAM Key-Value Store	2021	VLDB	8.3698208e-05
2,664	Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores	2020	SIGMOD	8.1569551e-05
2,837	SNARF: A Learning-Enhanced Range Filter	2022	VLDB	7.9527715e-05
2,868	Spooky: Granulating LSM-Tree Compactions Correctly	2022	VLDB	7.9241972e-05
2,920	What Modern NVMe Storage Can Do, And How To Exploit It: High-Performance I/O for High-Performance Storage Engines	2023	VLDB	7.8540089e-05
3,826	ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA	2022	SIGMOD	6.9984204e-05
4,197	Proteus: A Self-Designing Range Filter	2022	SIGMOD	6.7417716e-05
4,685	Enabling Low Tail Latency on Multicore Key-Value Stores	2020	VLDB	6.4713469e-05
5,046	Dissecting, Designing, and Optimizing LSM-based Data Stores	2022	SIGMOD	6.3000825e-05
5,253	ByteHTAP: ByteDance’s HTAP System with High Data Freshness and Strong Data Consistency	2022	VLDB	6.2080572e-05
6,885	Border-Collie: A Wait-free, Read-optimal Algorithm for Database Logging on Multicore Hardware	2019	SIGMOD	5.6560837e-05

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