Mach: A Pluggable Metrics Storage Engine for the Age of Observability
Summary: Mach: a pluggable, RocksDB-style metrics storage engine tailored to observability workloads; its lean, loosely-coordinated design exploits metrics semantics (append-heavy, high-cardinality, short retention) to optimize ingestion and query paths. Preliminary results: ~10× write and ~3× read throughput vs popular TSDBs. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Franco Solleza (Brown University)
- 2. Andrew Crotty (Brown University; Carnegie Mellon University)
- 3. Suman Karumuri (Slack Technologies)
- 4. Nesime Tatbul (Intel; Massachusetts Institute of Technology)
- 5. Stan Zdonik (Brown University)
BibTeX Citation
@inproceedings{solleza_cidr22,
address = {Amsterdam, Netherlands},
series = {{CIDR} '22},
title = {{Mach: A Pluggable Metrics Storage Engine for the Age of Observability}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Solleza, Franco and Crotty, Andrew and Karumuri, Suman and Tatbul, Nesime and Zdonik, Stan},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,324 | Mach: Firefighting Time-Critical Issues in Complex Systems Using High-Frequency Telemetry | 2024 | VLDB | 5.093636e-05 |
| 11,395 | ForestTI: A Scalable Inverted-Index-Oriented Timeseries Management System with Flexible Memory Efficiency | 2023 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 49 | Weaving Relations for Cache Performance | 2001 | VLDB | 0.00043781096 |
| 103 | DuckDB: an Embeddable Analytical Database | 2019 | SIGMOD | 0.00034161428 |
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.00029250767 |
| 669 | The TileDB Array Data Storage Manager | 2017 | VLDB | 0.00015163245 |
| 1,242 | Druid: A Real-time Analytical Data Store | 2014 | SIGMOD | 0.00011516162 |
| 3,092 | DeepSqueeze: Deep Semantic Compression for Tabular Data | 2020 | SIGMOD | 7.7679406e-05 |
| 3,123 | Monarch: Google’s Planet-Scale In-Memory Time Series Database | 2020 | VLDB | 7.7354933e-05 |
| 3,326 | Timon: A Timestamped Event Database for Efficient Telemetry Data Processing and Analytics | 2020 | SIGMOD | 7.5187553e-05 |
| 6,336 | Heracles: An Efficient Storage Model and Data Flushing for Performance Monitoring Timeseries | 2021 | VLDB | 5.9088937e-05 |
| 13,434 | Cloud Observability: A MELTing Pot for Petabytes of Heterogenous Time Series | 2021 | CIDR | - |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,498 | LeanStore: A High-Performance Storage Engine for NVMe SSDs | 2024 | VLDB |
| 2 | 7,821 | Concurrent Log-Structured Memory for Many-Core Key-Value Stores | 2018 | VLDB |
| 3 | 4,993 | Key-Value Storage Engines | 2020 | SIGMOD |
| 4 | 3,963 | Solving Big Data Challenges for Enterprise Application Performance Management | 2012 | VLDB |
| 5 | 8,240 | Magma: A High Data Density Storage Engine Used in Couchbase | 2022 | VLDB |
| 6 | 6,336 | Heracles: An Efficient Storage Model and Data Flushing for Performance Monitoring Timeseries | 2021 | VLDB |
| 7 | 1,792 | MacroBase: Prioritizing Attention in Fast Data | 2017 | SIGMOD |
| 8 | 11,823 | A Drop-in Middleware for Serializable DB Clustering across Geo-distributed Sites | 2020 | VLDB |
| 9 | 11,009 | Goku: A Schemaless Time Series Database for Large Scale Monitoring at Pinterest | 2025 | VLDB |
| 10 | 11,324 | Mach: Firefighting Time-Critical Issues in Complex Systems Using High-Frequency Telemetry | 2024 | VLDB |