Mach: Firefighting Time-Critical Issues in Complex Systems Using High-Frequency Telemetry
Summary: Mach is an on-host storage engine for lossless, near-real-time collection and querying of high-frequency eBPF telemetry under tight resource limits. Its Temporal Skip Log provides lightweight, write-optimized ingestion with immediate queryability, outperforming conventional time-series systems. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Franco Solleza (Brown University)
- 2. Shihang Li (University of Washington)
- 3. William Sun (Brown University)
- 4. Richard Tang (Brown University)
- 5. Malte Schwarzkopf (Brown University)
- 6. Nesime Tatbul (Intel; Massachusetts Institute of Technology)
- 7. Andrew Crotty (Northwestern University)
- 8. David Cohen (Intel)
- 9. Stan Zdonik (Brown University)
BibTeX Citation
@article{solleza_vldb24,
title = {{Mach: Firefighting Time-Critical Issues in Complex Systems Using High-Frequency Telemetry}},
author = {Solleza, Franco and Li, Shihang and Sun, William and Tang, Richard and Schwarzkopf, Malte and Tatbul, Nesime and Crotty, Andrew and Cohen, David and Zdonik, Stan},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4425--4428},
doi = {10.14778/3685800.3685891},
url = {https://doi.org/10.14778/3685800.3685891},
year = {2024}
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,615 | Apache IoTDB: Time-series Database for Internet of Things | 2020 | VLDB | 0.00010185068 |
| 7,199 | FishStore: Fast Ingestion and Indexing of Raw Data | 2019 | VLDB | 5.6610618e-05 |
| 7,906 | Mach: A Pluggable Metrics Storage Engine for the Age of Observability | 2022 | CIDR | 5.5046335e-05 |
| 7,964 | Dendrite: Bolt-on Adaptivity for Data Systems | 2021 | SIGMOD | 5.4950268e-05 |
| 7,967 | Sentinel: Understanding Data Systems | 2020 | SIGMOD | 5.4950268e-05 |
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