FEBench: A Benchmark for Real-Time Relational Data Feature Extraction
Summary: Analyzes real-time relational feature extraction (RTFE) workloads across 100+ public and industrial datasets, showing RTFE's SQL-like queries have markedly different operator mixes, query shapes, and latency/tail sensitivity than traditional DB benchmarks. Presents FEBench — a Gray-compliant domain benchmark with representative datasets, query templates, and an online request simulator — and uses it to compare OpenMLDB and Flink, revealing distinct latency and concurrency trade-offs. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xuanhe Zhou
- 2. Cheng Chen
- 3. Kunyi Li
- 4. Bingsheng He
- 5. Mian Lu
- 6. Qiaosheng Liu
- 7. Wei Huang
- 8. Guoliang Li
- 9. Zhao Zheng
- 10. Yuqiang Chen
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,750 | Breaking It Down: An In-depth Study of Index Advisors | 2024 | VLDB | 4.9392771e-05 |
| 8,080 | Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines | 2024 | VLDB | 4.5911668e-05 |
| 10,177 | InferF: Declarative Factorization of AI/ML Inferences over Joins | 2026 | SIGMOD | 4.1945683e-05 |
| 10,411 | OpenMLDB: A Real-Time Relational Data Feature Computation System for Online ML | 2025 | SIGMOD | 4.1945683e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next