Dandelion: Smaller Clusters, Bigger Speeds—Distributed Transactions Redefined
Summary: Dandelion: an in-memory, RDMA-enabled transactional KVS that exploits small-cluster (5–10 nodes) locality via per-recipient packet batching, batched hashtable access with software prefetching, and strongly-consistent local reads from backups. Up to 6.5× throughput vs FaSST at 5 nodes (3.5× at 10) on OLTP workloads. (summarized by gpt-5-mini on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 635 | Staring into the Abyss: An Evaluation of Concurrency Control with One Thousand Cores | 2015 | VLDB | 0.00018879031 |
| 1,361 | The End of Slow Networks: It's Time for a Redesign | 2016 | VLDB | 0.00012379741 |
| 1,819 | The End of a Myth: Distributed Transactions Can Scale | 2017 | VLDB | 0.00010429773 |
| 4,283 | Fast General Distributed Transactions with Opacity | 2019 | SIGMOD | 6.2917189e-05 |
| 5,064 | G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture | 2022 | VLDB | 5.7261007e-05 |
| 5,512 | Strong consistency is not hard to get: Two-Phase Locking and Two-Phase Commit on Thousands of Cores | 2019 | VLDB | 5.4665318e-05 |
| 5,966 | Cornus: Atomic Commit for a Cloud DBMS with Storage Disaggregation | 2023 | VLDB | 5.2517881e-05 |
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