Databases Unbound: Querying All of the World’s Bytes with AI
Summary: Argues that AI-powered semantic extraction can bring unstructured text, images, and video into database querying. Advocates declarative AI data systems to address scalability, correctness, and reliability, illustrated by document/video systems and research challenges. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Samuel Madden (Massachusetts Institute of Technology)
- 2. Michael Cafarella (Massachusetts Institute of Technology)
- 3. Michael Franklin (University of Chicago)
- 4. Tim Kraska (Massachusetts Institute of Technology)
BibTeX Citation
@article{madden_vldb24,
title = {{Databases Unbound: Querying All of the World’s Bytes with AI}},
author = {Madden, Samuel and Cafarella, Michael and Franklin, Michael and Kraska, Tim},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4546--4554},
doi = {10.14778/3685800.3685916},
url = {https://doi.org/10.14778/3685800.3685916},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,142 | AOP: Automated and Interactive LLM Pipeline Orchestration for Answering Complex Queries | 2025 | CIDR | 6.7814795e-05 |
| 7,885 | Semantic Integrity Constraints: Declarative Guardrails for AI-Augmented Data Processing Systems | 2025 | VLDB | 5.433531e-05 |
| 9,304 | Sphinteract: Resolving Ambiguities in NL2SQL Through User Interaction | 2025 | VLDB | 5.1978532e-05 |
| 10,422 | Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data | 2026 | SIGMOD | 4.9793485e-05 |
| 10,622 | Beyond Relational: Semantic-Aware Multi-Modal Analytics with LLM-Native Query Optimization | 2026 | SIGMOD | 4.9793485e-05 |
| 11,034 | Data Agents: Rethinking Data Systems in the AI Agent Era | 2026 | VLDB | 4.9793485e-05 |
| 11,069 | KEN: An Execution Engine for Unstructured Database Systems | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 1 | 3,282 | A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems | 2021 | SIGMOD |
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| 4 | 11,808 | Towards Auto-Generated Data Systems | 2023 | VLDB |
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| 8 | 2,908 | AI Meets Database: AI4DB and DB4AI | 2021 | SIGMOD |
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| 10 | 13,668 | Turning Databases Into Generative AI Machines | 2024 | CIDR |