{"slug": "rrdtool", "name": "rrdtool", "category": "observability", "category_name": "Monitoring and analytics", "description": "", "recommenders": 1, "commenters": 2, "warners": 0, "score": 1.136, "rising": -0.33, "first": "2026-03-07", "latest": "2026-06-20", "why": "", "why_is_quote": false, "has_verdict": false, "sentiment": {"recommend": 1, "neutral": 1, "compare": 0, "warn": 0}, "spark": [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], "listed": false, "loved": [], "caveat": "", "short_quote": "", "icon": false, "domain": null, "github_repo": null, "official_url": "", "pricing": "", "aliases": ["rrdtool", "RRDtool"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 756654528, "item_id": 47290908, "url": "https://news.ycombinator.com/item?id=47290908", "by": "plagiat0r", "date": "2026-03-07", "stance": "recommend", "quote": "I use rrdtool to this day, as a building block", "excerpt": "Back in the 90/2000 the was a very popular tool named rrdtool to store metrics in a round robin structure on disk, especially suited for network metrics. The goal of the storage was to have a fixed size and cover only last NNN days, circularly. I use rrdtool to this day, as a building block, but this project looks much better.", "context": "", "use_case": "metrics storage", "switched_from": "", "story": "Show HN: Kula \u2013 Lightweight, self-contained Linux server monitoring tool"}]}], "caveats": [], "who": [], "tags": [], "use_cases": ["time-series storage", "metrics storage"], "compared": [{"slug": "mysql", "name": "MySQL", "co": 1, "switched_from": 0, "switched_to": 1}], "makers": [], "threads": [{"url": "https://news.ycombinator.com/item?id=48553388", "title": "DuckDB Internals: Why Is DuckDB Fast? (Part 1)", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47282807", "title": "Show HN: Kula \u2013 Lightweight, self-contained Linux server monitoring tool", "mentions": 1}], "sentiment_by_month": {"2025-11": {}, "2025-12": {}, "2026-01": {}, "2026-02": {}, "2026-03": {"recommend": 1}, "2026-04": {}, "2026-05": {}, "2026-06": {"neutral": 1}, "2026-07": {}, "2026-08": {}, "2026-09": {}, "2026-10": {}}, "quotes": [{"id": 777741793, "item_id": 48608862, "url": "https://news.ycombinator.com/item?id=48608862", "by": "My_Name", "date": "2026-06-20", "stance": "neutral", "quote": "I used to use RRDTool in python", "excerpt": "One of my projects was using a RRD database to store 10-second samples from 20 data streams with a RRD time of 1 year, which works out to around 82 million entries. I display this interactively on a raspberry pi and I used to use RRDTool in python, but switching to my own code leveraging mySQL (and using some judicious rollup tables) means that instead of a larger time span taking ~5 seconds to update, it is now fast", "context": "", "use_case": "time-series storage", "switched_from": "", "story": "DuckDB Internals: Why Is DuckDB Fast? (Part 1)"}, {"id": 756654528, "item_id": 47290908, "url": "https://news.ycombinator.com/item?id=47290908", "by": "plagiat0r", "date": "2026-03-07", "stance": "recommend", "quote": "I use rrdtool to this day, as a building block", "excerpt": "Back in the 90/2000 the was a very popular tool named rrdtool to store metrics in a round robin structure on disk, especially suited for network metrics. The goal of the storage was to have a fixed size and cover only last NNN days, circularly. I use rrdtool to this day, as a building block, but this project looks much better.", "context": "", "use_case": "metrics storage", "switched_from": "", "story": "Show HN: Kula \u2013 Lightweight, self-contained Linux server monitoring tool"}]}