Declarative and distributed graph analytics with GRADOOP
Summary: Gradoop combines graph DB capabilities with distributed graph processing to enable declarative, scalable graph analytics. It exposes graph pattern matching and graph grouping operators, supports up to 10B edges, and runs locally or on clusters as an open-source framework. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Martin Junghanns
- 2. Max Kießling
- 3. Niklas Teichmann
- 4. Kevin Gómez
- 5. André Petermann
- 6. Erhard Rahm
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0019040811 |
| 530 | The LDBC Social Network Benchmark: Interactive Workload | 2015 | SIGMOD | 0.00020823189 |
| 5,517 | Managing and Mining Large Graphs: Systems and Implementations | 2012 | SIGMOD | 5.4685314e-05 |
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