SeeDB: Visualizing Database Queries Efficiently
Summary: SeeDB extends DBMS optimization to jointly explore the space of query plans and possible result visualizations. It outputs recommended visualizations paired with suitable execution plans, automating visualization discovery and outlining a research agenda for future work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Aditya Parameswaran (Stanford University; University of Illinois Urbana-Champaign)
- 2. Neoklis Polyzotis (Google; University of California Santa Cruz)
- 3. Hector Garcia-Molina (Stanford University)
BibTeX Citation
@article{parameswaran_vldb14,
title = {{SeeDB: Visualizing Database Queries Efficiently}},
author = {Parameswaran, Aditya and Polyzotis, Neoklis and Garcia-Molina, Hector},
journal = {PVLDB},
series = {{VLDB} '14},
volume = {7},
number = {4},
pages = {325--336},
doi = {10.14778/2732240.2732248},
url = {https://doi.org/10.14778/2732240.2732248},
year = {2014}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 395 | SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics | 2015 | VLDB | 0.00019125046 |
| 1,220 | Overview of Data Exploration Techniques | 2015 | SIGMOD | 0.00011449992 |
| 1,668 | Rapid Sampling for Visualizations with Ordering Guarantees | 2015 | VLDB | 9.9190265e-05 |
| 4,455 | ASAP: Prioritizing Attention via Time Series Smoothing | 2017 | VLDB | 6.5772404e-05 |
| 5,003 | SeeDB: Automatically Generating Query Visualizations | 2014 | VLDB | 6.306747e-05 |
| 5,203 | The Case for Data Visualization Management Systems | 2014 | VLDB | 6.2172569e-05 |
| 6,530 | Fast-Forwarding to Desired Visualizations with zenvisage | 2017 | CIDR | 5.7368132e-05 |
| 12,127 | AUDITOR: A System Designed for Automatic Discovery of Complex Integrity Constraints in Relational Databases | 2020 | SIGMOD | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Online Aggregation | 1997 | SIGMOD | 0.00076079812 |
| 268 | Distinct Sampling for Highly-Accurate Answers to Distinct Values Queries and Event Reports | 2001 | VLDB | 0.00022654182 |
| 311 | Approximate Query Processing Using Wavelets | 2000 | VLDB | 0.00021315058 |
| 700 | Explaining differences in multidimensional aggregates | 1999 | VLDB | 0.00014642224 |
| 929 | Intelligent Rollups in Multidimensional OLAP Data | 2001 | VLDB | 0.000130092 |
| 986 | User-adaptive exploration of multidimensional data | 2000 | VLDB | 0.00012645438 |
| 1,095 | Scalable Approximate Query Processing With The DBO Engine | 2007 | SIGMOD | 0.00012036913 |
| 1,114 | Google Fusion Tables: Web-Centered Data Management and Collaboration | 2010 | SIGMOD | 0.00011939972 |
| 2,657 | DEVise: Integrated Querying and Visual Exploration of Large Datasets | 1997 | SIGMOD | 8.1460696e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 5,203 | The Case for Data Visualization Management Systems | 2014 | VLDB |
| 2 | 5,314 | Databases and Visualization | 1996 | SIGMOD |
| 3 | 14,632 | VisDB: A System for Visualizing Large Databases | 1995 | SIGMOD |
| 4 | 7,249 | QueryScope: Visualizing Queries for Repeatable Database Tuning | 2008 | VLDB |
| 5 | 3,062 | Towards a Hands-Free Query Optimizer through Deep Learning | 2019 | CIDR |
| 6 | 13,923 | Data Visualization Management Systems | 2015 | CIDR |
| 7 | 7,597 | Interactive Plan Hints for Query Optimization | 2009 | SIGMOD |
| 8 | 8,359 | Databases will Visualize Queries too | 2011 | VLDB |
| 9 | 395 | SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics | 2015 | VLDB |
| 10 | 5,003 | SeeDB: Automatically Generating Query Visualizations | 2014 | VLDB |