{"slug": "libsql", "name": "libsql", "category": "databases", "category_name": "Databases", "description": "", "recommenders": 3, "commenters": 3, "warners": 0, "score": 2.653, "rising": -0.98, "first": "2026-03-03", "latest": "2026-07-14", "why": "Moved from SQLite to libsql for native vector search.", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 3, "neutral": 0, "compare": 0, "warn": 0}, "spark": [0, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0], "listed": true, "loved": [], "caveat": "", "short_quote": "Moved from SQLite to libsql for native vector search.", "icon": true, "domain": null, "github_repo": null, "official_url": "https://github.com/tursodatabase/libsql", "pricing": "", "aliases": ["libsql", "libSQL", "LibSQL"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 782498128, "item_id": 48906133, "url": "https://news.ycombinator.com/item?id=48906133", "by": "afonsosoares", "date": "2026-07-14", "stance": "recommend", "quote": "you can have a sqld instance on a different VM with S3 backup.", "excerpt": "I could not agree more KISS is always the way to go. For those people that are interested you can have a sqld instance on a different VM with S3 backup. On my case I use k8s and the backend pod use rust libsqld crate with local first sql database file with remote sync to sqld. When pod start if db file is not available libsqld will try recover it from slqd otherwise it will just load local db file and sync.", "context": "runs backend pods on k8s", "use_case": "local-first database with remote sync", "switched_from": "", "story": "SQLite Is All You Need"}, {"id": 757131665, "item_id": 47320729, "url": "https://news.ycombinator.com/item?id=47320729", "by": "zanfiel", "date": "2026-03-10", "stance": "recommend", "quote": "Moved from SQLite to libsql for native vector search.", "excerpt": "OP edit: big update since I first posted this. Engram went from ~2,300 lines to 6,200+. Main changes: Replaced the flat 30-day exponential decay with FSRS-6 (same spaced repetition algorithm behind modern Anki, 21 parameters, trained on hundreds of millions of reviews). Every memory access is an implicit review now \u2014 stuff agents actually use builds stability, stuff they don't fades out naturally. Power-law forgettin", "context": "", "use_case": "vector search in Engram", "switched_from": "SQLite", "story": "Show HN: Engram \u2013 open-source persistent memory for AI agents (Bun and SQLite)"}, {"id": 755886641, "item_id": 47242915, "url": "https://news.ycombinator.com/item?id=47242915", "by": "SL1C3DL4BS", "date": "2026-03-03", "stance": "recommend", "quote": "I needed the database to be fast, local, and causal-consistent, so I used LibSQL.", "excerpt": "Hey HN, I got tired of seeing AI startups deploy autonomous agents that are one hallucination away from a catastrophic lawsuit. With the EU AI Act enforcement kicking in this year (August 2026), the current \"prompt engineering\" approach to AI safety isn't going to hold up in court. So, I built Vericore OS. It\u2019s an open-source, API-first compliance primitive that physically and cryptographically forces AI agents to be", "context": "", "use_case": "audit log database", "switched_from": "", "story": "Show HN: Vericore OS \u2013 A cryptographic containment field for AI"}]}], "caveats": [], "who": [{"by": "afonsosoares", "context": "runs backend pods on k8s", "url": "https://news.ycombinator.com/item?id=48906133", "date": "2026-07-14"}], "tags": [], "use_cases": ["local-first database with remote sync", "vector search in engram", "audit log database"], "compared": [{"slug": "sqlite", "name": "SQLite", "co": 2, "switched_from": 1, "switched_to": 0}], "makers": [], "threads": [{"url": "https://news.ycombinator.com/item?id=48905491", "title": "SQLite Is All You Need", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47307497", "title": "Show HN: Engram \u2013 open-source persistent memory for AI agents (Bun and SQLite)", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=47242905", "title": "Show HN: Vericore OS \u2013 A cryptographic containment field for AI", "mentions": 1}], "sentiment_by_month": {"2025-11": {}, "2025-12": {}, "2026-01": {}, "2026-02": {}, "2026-03": {"recommend": 2}, "2026-04": {}, "2026-05": {}, "2026-06": {}, "2026-07": {"recommend": 1}, "2026-08": {}, "2026-09": {}, "2026-10": {}}, "quotes": [{"id": 782498128, "item_id": 48906133, "url": "https://news.ycombinator.com/item?id=48906133", "by": "afonsosoares", "date": "2026-07-14", "stance": "recommend", "quote": "you can have a sqld instance on a different VM with S3 backup.", "excerpt": "I could not agree more KISS is always the way to go. For those people that are interested you can have a sqld instance on a different VM with S3 backup. On my case I use k8s and the backend pod use rust libsqld crate with local first sql database file with remote sync to sqld. When pod start if db file is not available libsqld will try recover it from slqd otherwise it will just load local db file and sync.", "context": "runs backend pods on k8s", "use_case": "local-first database with remote sync", "switched_from": "", "story": "SQLite Is All You Need"}, {"id": 757131665, "item_id": 47320729, "url": "https://news.ycombinator.com/item?id=47320729", "by": "zanfiel", "date": "2026-03-10", "stance": "recommend", "quote": "Moved from SQLite to libsql for native vector search.", "excerpt": "OP edit: big update since I first posted this. Engram went from ~2,300 lines to 6,200+. Main changes: Replaced the flat 30-day exponential decay with FSRS-6 (same spaced repetition algorithm behind modern Anki, 21 parameters, trained on hundreds of millions of reviews). Every memory access is an implicit review now \u2014 stuff agents actually use builds stability, stuff they don't fades out naturally. Power-law forgettin", "context": "", "use_case": "vector search in Engram", "switched_from": "SQLite", "story": "Show HN: Engram \u2013 open-source persistent memory for AI agents (Bun and SQLite)"}, {"id": 755886641, "item_id": 47242915, "url": "https://news.ycombinator.com/item?id=47242915", "by": "SL1C3DL4BS", "date": "2026-03-03", "stance": "recommend", "quote": "I needed the database to be fast, local, and causal-consistent, so I used LibSQL.", "excerpt": "Hey HN, I got tired of seeing AI startups deploy autonomous agents that are one hallucination away from a catastrophic lawsuit. With the EU AI Act enforcement kicking in this year (August 2026), the current \"prompt engineering\" approach to AI safety isn't going to hold up in court. So, I built Vericore OS. It\u2019s an open-source, API-first compliance primitive that physically and cryptographically forces AI agents to be", "context": "", "use_case": "audit log database", "switched_from": "", "story": "Show HN: Vericore OS \u2013 A cryptographic containment field for AI"}]}