Rafiki: Machine Learning as an Analytics Service System

Summary: Rafiki provides ML as an analytics service, decoupling training and inference from DB engines. It enables distributed hyper-parameter tuning for training and online ensemble inference to balance latency and accuracy. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12012
Venue: VLDB
Year: 2019
Pagerank: 6.8908973e-05
Overall Rank: 4,118 | 71.75%
DOI: 10.14778/3282495.3282499

Incoming Non-self Citations Over Time

Authors

1. Wei Wang (National University of Singapore)
2. Jinyang Gao (National University of Singapore)
3. Meihui Zhang (Beijing Institute of Technology)
4. Sheng Wang (National University of Singapore)
5. Gang Chen (Zhejiang University)
6. Teck Khim Ng (National University of Singapore)
7. Beng Chin Ooi (National University of Singapore)
8. Jie Shao (University of Electronic Science and Technology of China)
9. Moaz Reyad (National University of Singapore)

BibTeX Citation

@article{wang_vldb19,
        title = {{Rafiki: Machine Learning as an Analytics Service System}},
        author = {Wang, Wei and Gao, Jinyang and Zhang, Meihui and Wang, Sheng and Chen, Gang and Ng, Teck Khim and Ooi, Beng Chin and Shao, Jie and Reyad, Moaz},
        journal = {PVLDB},
        series = {{VLDB} '19},
        volume = {12},
        number = {2},
        pages = {128--140},
        doi = {10.14778/3282495.3282499},
        url = {https://doi.org/10.14778/3282495.3282499},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,865	End-to-end Optimization of Machine Learning Prediction Queries	2022	SIGMOD	8.0180243e-05
4,067	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches	2021	VLDB	6.9293511e-05
4,114	Optimizing Machine Learning Inference Queries with Correlative Proxy Models	2022	VLDB	6.8941194e-05
6,708	Serving Deep Learning Models with Deduplication from Relational Databases	2022	VLDB	5.7964983e-05
7,114	Serverless Data Science - Are We There Yet? A Case Study of Model Serving	2022	SIGMOD	5.6982359e-05
7,473	The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development	2020	SIGMOD	5.609366e-05
7,847	Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines	2024	VLDB	5.5330423e-05
9,290	Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale	2022	VLDB	5.2910774e-05
9,470	Powering In-Database Dynamic Model Slicing for Structured Data Analytics	2024	VLDB	5.2634238e-05
9,473	FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data	2023	SIGMOD	5.2634238e-05
10,623	KEN: An Execution Engine for Unstructured Database Systems	2026	VLDB	5.093636e-05
10,827	A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty	2025	VLDB	5.093636e-05
11,209	Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems	2024	VLDB	5.093636e-05
11,735	Quality of Sentiment Analysis Tools: The Reasons of Inconsistency	2021	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
284	NoScope: Optimizing Neural Network Queries over Video at Scale	2017	VLDB	0.00022370521
641	Relational Cloud: A Database-as-a-Service for the Cloud	2011	CIDR	0.00015400863
2,029	Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads	2018	VLDB	9.2843642e-05
3,678	Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?	2015	SIGMOD	7.207554e-05
6,128	GEMINI: An Integrative Healthcare Analytics System	2014	VLDB	5.9668307e-05

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