ReStore - Neural Data Completion for Relational Databases
Summary: ReStore uses neural, schema-structured completion for relational tables with missing tuples to synthesize plausible substitutes. It reduces aggregate-query error by up to 390% vs incomplete data alone, enabling automated OLAP without manual imputation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Benjamin Hilprecht (Technical University of Darmstadt)
- 2. Carsten Binnig (Technical University of Darmstadt)
BibTeX Citation
@inproceedings{hilprecht_sigmod21,
title = {{ReStore - Neural Data Completion for Relational Databases}},
author = {Hilprecht, Benjamin and Binnig, Carsten},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457264},
url = {https://dl.acm.org/doi/10.1145/3448016.3457264},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,680 | Controllable Tabular Data Synthesis Using Diffusion Models | 2024 | SIGMOD | 5.7104433e-05 |
| 10,181 | In-Database Data Imputation | 2024 | SIGMOD | 5.0653015e-05 |
| 11,590 | Enriching Relations with Additional Attributes for ER | 2024 | VLDB | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 13,746 | Using Deep Learning Models to Replace Large Materialized Views in Relational Database | 2021 | CIDR |
| 2 | 11,683 | Querying Incomplete Numerical Data: Between Certain and Possible Answers | 2023 | PODS |
| 3 | 8,679 | Relational Deep Dive: Error-Aware Queries Over Unstructured Data | 2026 | VLDB |
| 4 | 861 | SnipSuggest: Context-Aware Autocompletion for SQL | 2011 | VLDB |
| 5 | 1,714 | Spreadsheets in RDBMS for OLAP | 2003 | SIGMOD |
| 6 | 4,707 | PreQR: Pre-training Representation for SQL Understanding | 2022 | SIGMOD |
| 7 | 11,239 | Holistic query Approximation via RL Modeling | 2025 | VLDB |
| 8 | 5,739 | Capturing Missing Tuples and Missing Values | 2010 | PODS |
| 9 | 10,853 | Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models | 2026 | VLDB |
| 10 | 6,146 | Identifying the Extent of Completeness of Query Answers over Partially Complete Databases | 2015 | SIGMOD |