Ringo: Interactive Graph Analytics on Big-Memory Machines
Summary: Ringo enables interactive graph analytics on a single big-memory machine. It ingests relational tables to build graphs and offers 200+ analytics functions, delivering high performance with easy, iterative data exploration for graph workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yonathan Perez (Stanford University)
- 2. Rok Sosič (Stanford University)
- 3. Arijit Banerjee (Stanford University)
- 4. Rohan Puttagunta (Stanford University)
- 5. Martin Raison (Stanford University)
- 6. Pararth Shah (Stanford University)
- 7. Jure Leskovec (Stanford University)
BibTeX Citation
@inproceedings{perez_sigmod15,
title = {{Ringo: Interactive Graph Analytics on Big-Memory Machines}},
author = {Perez, Yonathan and Sosič, Rok and Banerjee, Arijit and Puttagunta, Rohan and Raison, Martin and Shah, Pararth and Leskovec, Jure},
series = {{SIGMOD} '15},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2723372.2735369},
url = {https://dl.acm.org/doi/10.1145/2723372.2735369},
year = {2015}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,854 | Extracting and Analyzing Hidden Graphs from Relational Databases | 2017 | SIGMOD | 8.0350257e-05 |
| 4,973 | GraphGen: Exploring Interesting Graphs in Relational Data | 2015 | VLDB | 6.4187713e-05 |
| 9,944 | Chimera: A system design of dual storage and traversal-join unified query processing for SQL/PGQ | 2025 | VLDB | 5.1915905e-05 |
| 12,075 | Graph-based Exploration of Non-graph Datasets | 2016 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0012250108 |
| 20 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.00056944564 |
| 436 | Trinity: A Distributed Graph Engine on a Memory Cloud | 2013 | SIGMOD | 0.00018504439 |
| 1,300 | An Experimental Comparison of Pregel-like Graph Processing Systems | 2014 | VLDB | 0.00011258552 |
| 1,654 | Navigating the Maze of Graph Analytics Frameworks using Massive Graph Datasets | 2014 | SIGMOD | 0.00010104703 |
| 3,008 | Scalable Big Graph Processing in MapReduce | 2014 | SIGMOD | 7.8578871e-05 |
| 3,393 | OPT: A New Framework for Overlapped and Parallel Triangulation in Large-scale Graphs | 2014 | SIGMOD | 7.45141e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,380 | MiniGraph: Querying Big Graphs with a Single Machine | 2023 | VLDB |
| 2 | 5,567 | iTurboGraph: Scaling and Automating Incremental Graph Analytics | 2021 | SIGMOD |
| 3 | 9,534 | HiNGE: Enabling Temporal Network Analytics at Scale | 2013 | SIGMOD |
| 4 | 11,714 | RealGraphWeb: A Graph Analysis Platform on the Web | 2021 | VLDB |
| 5 | 10,037 | Graph Exploration: From Users to Large Graphs | 2017 | SIGMOD |
| 6 | 1,654 | Navigating the Maze of Graph Analytics Frameworks using Massive Graph Datasets | 2014 | SIGMOD |
| 7 | 4,787 | Systems for Big-Graphs | 2014 | VLDB |
| 8 | 11,859 | GraphWrangler: An Interactive Graph View on Relational Data | 2019 | SIGMOD |
| 9 | 13,289 | Effective Clustering for Large Multi-Relational Graphs | 2026 | SIGMOD |
| 10 | 9,447 | Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool | 2015 | VLDB |