GraphWrangler: An Interactive Graph View on Relational Data
Summary: GraphWrangler connects to an RDBMS to extract graphs from relational data, enabling visualization and interactive exploration with no manual ETL. It automatically generates ETL scripts and relies on a predictive interaction framework plus a SQL-subset data transformation language for interactive graph analytics. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Nafisa Anzum
- 2. Semih Salihoglu
- 3. Daniel Vogel
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,600 | Making RDBMSs Efficient on Graph Workloads Through Predefined Joins | 2022 | VLDB | 4.4876776e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 331 | The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing | 2018 | VLDB | 0.00027214222 |
| 1,756 | Graphflow: An Active Graph Database | 2017 | SIGMOD | 0.00010664542 |
| 2,048 | Graph Cube: On Warehousing and OLAP Multidimensional Networks | 2011 | SIGMOD | 9.6914395e-05 |
| 2,097 | Predictive Interaction for Data Transformation | 2015 | CIDR | 9.5489822e-05 |
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