Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems
Summary: Feature stores for ML pipelines expand from traditional tabular features toward embedding ecosystems. It pinpoints embedding-specific gaps—training data management, embedding quality assessment, and downstream monitoring—that standard feature stores don’t cover, and surveys candidate solutions. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Laurel Orr (Stanford University)
- 2. Atindriyo Sanyal (Uber)
- 3. Xiao Ling (Apple)
- 4. Karan Goel (Stanford University)
- 5. Megan Leszczynski (Stanford University)
BibTeX Citation
@article{orr_vldb21,
title = {{Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems}},
author = {Orr, Laurel and Sanyal, Atindriyo and Ling, Xiao and Goel, Karan and Leszczynski, Megan},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {12},
pages = {3178--3181},
doi = {10.14778/3476311.3476402},
url = {https://doi.org/10.14778/3476311.3476402},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,449 | From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management | 2022 | VLDB | 6.697553e-05 |
| 5,704 | Optimizing Data Pipelines for Machine Learning in Feature Stores | 2023 | VLDB | 6.1146371e-05 |
| 6,538 | UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads | 2022 | VLDB | 5.8477764e-05 |
| 8,244 | SHiFT: An Efficient, Flexible Search Engine for Transfer Learning | 2023 | VLDB | 5.4587712e-05 |
| 9,433 | FEBench: A Benchmark for Real-Time Relational Data Feature Extraction | 2023 | VLDB | 5.2696166e-05 |
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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 |
|---|---|---|---|---|
| 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00027191081 |
| 205 | Snorkel: Rapid Training Data Creation with Weak Supervision | 2018 | VLDB | 0.00025235185 |
| 1,121 | ARDA: Automatic Relational Data Augmentation for Machine Learning | 2020 | VLDB | 0.00012093059 |
| 3,947 | Overton: A Data System for Monitoring and Improving Machine-Learned Products | 2020 | CIDR | 7.0040437e-05 |
| 9,614 | Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation | 2021 | CIDR | 5.2444447e-05 |
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| 2 | 11,512 | Towards Observability for Machine Learning Pipelines | 2022 | CIDR |
| 3 | 1,250 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD |
| 4 | 2,657 | Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities | 2021 | SIGMOD |
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| 6 | 11,066 | ML-Asset Management: Curation, Discovery, and Utilization | 2025 | VLDB |
| 7 | 1,147 | Data Management Challenges in Production Machine Learning | 2017 | SIGMOD |
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