SEER: An End-to-End Toolkit for Benchmarking Time Series Database Systems in Monitoring Applications
Summary: SEER/TSM-Bench: end-to-end toolkit/dashboard for TSDB benchmarking in monitoring, with configurable query portfolios, workload mixes, feature-contamination, and synthetic data augmentation. Automates experiments (latency, throughput, ingest, compression, scalability), recommends best system per use-case; open-source with preloaded results. (summarized by gpt-5-mini on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,641 | Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science | 2018 | VLDB | 8.3905374e-05 |
| 5,071 | Time Series Data Encoding for Efficient Storage: A Comparative Analysis in Apache IoTDB | 2022 | VLDB | 5.7188461e-05 |
| 6,280 | Self-supervised and Interpretable Data Cleaning with Sequence Generative Adversarial Networks | 2023 | VLDB | 5.1290457e-05 |
| 6,425 | A Deep Generative Model for Trajectory Modeling and Utilization | 2023 | VLDB | 5.0670573e-05 |
| 6,955 | Inspector Gadget: A Data Programming-based Labeling System for Industrial Images | 2021 | VLDB | 4.8864297e-05 |
| 7,399 | SmartBench: A Benchmark For Data Management In Smart Spaces | 2020 | VLDB | 4.7410149e-05 |
| 8,985 | TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications | 2023 | VLDB | 4.4156106e-05 |
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