Goku: A Schemaless Time Series Database for Large Scale Monitoring at Pinterest
Summary: Goku: schemaless TSDB using tiered storage and write-time aggregation to serve low-latency recent metrics and compact older data for cost-efficient retention. Per-metric TTL/rollup/backfill plus multi-replica S3-backed design for HA and operational flexibility. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Monil Mukesh Sanghavi (Pinterest Inc.)
- 2. Ming-May Hu (Pinterest Inc.)
- 3. Zhenxiao Luo (Pinterest Inc.)
- 4. Xiao Li (Pinterest Inc.)
- 5. Kapil Bajaj (Pinterest Inc.)
BibTeX Citation
@article{sanghavi_vldb25,
title = {{Goku: A Schemaless Time Series Database for Large Scale Monitoring at Pinterest}},
author = {Sanghavi, Monil Mukesh and Hu, Ming-May and Luo, Zhenxiao and Li, Xiao and Bajaj, Kapil},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {2},
pages = {503--515},
doi = {10.14778/3705829.3705862},
url = {https://doi.org/10.14778/3705829.3705862},
year = {2025}
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Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 148 | Gorilla: A Fast, Scalable, In-Memory Time Series Database | 2015 | VLDB | 0.0002900671 |
| 1,637 | Apache IoTDB: Time-series Database for Internet of Things | 2020 | VLDB | 0.00010013276 |
| 2,919 | Monarch: Google’s Planet-Scale In-Memory Time Series Database | 2020 | VLDB | 7.8548399e-05 |
| 3,382 | Timon: A Timestamped Event Database for Efficient Telemetry Data Processing and Analytics | 2020 | SIGMOD | 7.3559487e-05 |
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