{"slug": "meilisearch", "name": "Meilisearch", "category": "search", "category_name": "Search", "description": "", "recommenders": 1, "commenters": 3, "warners": 0, "score": 1.374, "rising": -0.33, "first": "2025-11-06", "latest": "2026-07-14", "why": "MeiliSearch can be used as a vector database for langchain.", "why_is_quote": true, "has_verdict": false, "sentiment": {"recommend": 1, "neutral": 2, "compare": 0, "warn": 0}, "spark": [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], "listed": false, "loved": [], "caveat": "", "short_quote": "MeiliSearch can be used as a vector database for langchain.", "icon": false, "domain": null, "github_repo": "github.com/meilisearch/meilisearch", "official_url": "https://github.com/meilisearch/meilisearch", "pricing": "", "aliases": ["Meilisearch"], "verdict": null, "praise": [{"label": "", "summary": "", "quotes": [{"id": 754549153, "item_id": 47159322, "url": "https://news.ycombinator.com/item?id=47159322", "by": "westurner", "date": "2026-02-25", "stance": "recommend", "quote": "MeiliSearch can be used as a vector database for langchain.", "excerpt": "Np. Still learning about how to reference agentskills from my coding LLM here. Haven't yet worked with MCP or A2A much. I should port instruction prompts from each project's AGENTS.md to reusable skills in .claude/skills/skillname/SKILL.md ; so that I can reference \"/skillname\" in a prompt to reuse that prompt text. Copilot looks for agent skills in .claude/skills/, .github/skills/, or .agents/skills/ . FWIU there ar", "context": "", "use_case": "search and vector database", "switched_from": "", "story": "Show HN: Saga \u2013 A Jira-like project tracker MCP server for AI agents (SQLite)"}]}], "caveats": [], "who": [{"by": "probst", "context": "runs a search service with edge nodes", "url": "https://news.ycombinator.com/item?id=48903452", "date": "2026-07-14"}], "tags": [], "use_cases": ["search indices across edge nodes", "search backend", "search and vector database", "search index for recommendation site"], "compared": [{"slug": "tantivy", "name": "Tantivy", "co": 1, "switched_from": 0, "switched_to": 1}, {"slug": "lmdb", "name": "LMDB", "co": 2, "switched_from": 0, "switched_to": 0}], "makers": [{"id": 780366656, "item_id": 48772916, "url": "https://news.ycombinator.com/item?id=48772916", "by": "Kerollmops", "date": "2026-07-03", "stance": "recommend", "quote": "We use this in Meilisearch [1] to post-process cache for our most common prefixes", "excerpt": "Yeah, and I also added support for parallel read your own writes where you can write tons of entries and spawn multi children read-only transactions from your writes where transaction and read from them in parallel. We use this in Meilisearch [1] to post-process cache for our most common prefixes i.e., \"w\" will match \"work\", \"word\"... and computing this requires doing large unions of the documents matching those word", "context": "Meilisearch developer", "use_case": "search engine", "switched_from": "", "story": "Lightning Memory-Mapped Database Manager (LMDB) 1.0"}, {"id": 780365985, "item_id": 48772874, "url": "https://news.ycombinator.com/item?id=48772874", "by": "Kerollmops", "date": "2026-07-03", "stance": "recommend", "quote": "Meilisearch (second most stared search engine on GitHub)", "excerpt": "I recently talked to Howard [1] about lies he was saying about Sanakirja, an LMDB-inspired disk allocator. That's always the same arguments: C is better than Rust for X, Y or Z reasons. While I reported a segfault just two weeks earlier... [2]. I love LMDB, we use it in Meilisearch (second most stared search engine on GitHub) [3] for about 7 years now. The main issues were related to write speed but we do a compactio", "context": "", "use_case": "search engine", "switched_from": "", "story": "Lightning Memory-Mapped Database Manager (LMDB) 1.0"}], "threads": [{"url": "https://news.ycombinator.com/item?id=48884984", "title": "Ask HN: What Are You Working On? (July 2026)", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=48766598", "title": "Lightning Memory-Mapped Database Manager (LMDB) 1.0", "mentions": 2}, {"url": "https://news.ycombinator.com/item?id=47106215", "title": "Show HN: Saga \u2013 A Jira-like project tracker MCP server for AI agents (SQLite)", "mentions": 1}, {"url": "https://news.ycombinator.com/item?id=45825733", "title": "Show HN: I scraped 3B Goodreads reviews to train a better recommendation model", "mentions": 1}], "sentiment_by_month": {"2025-11": {"neutral": 1}, "2025-12": {}, "2026-01": {}, "2026-02": {"recommend": 1}, "2026-03": {}, "2026-04": {}, "2026-05": {}, "2026-06": {}, "2026-07": {"neutral": 1}, "2026-08": {}, "2026-09": {}, "2026-10": {}}, "quotes": [{"id": 782455232, "item_id": 48903452, "url": "https://news.ycombinator.com/item?id=48903452", "by": "probst", "date": "2026-07-14", "stance": "neutral", "quote": "Meilisearch is a very good search application for sure, but our needs drifted apart.", "excerpt": "Long story short: Meilisearch is a very good search application for sure, but our needs drifted apart. Longer version: Our usecase isn't entirely aligned with how Meilisearch is meant to be used, I think. For one, we have a very high number of indices (at the time of using Meilisearch we had multiple per site that uses our service) and we wanted to have these replicated to edge nodes we have placed around the globe t", "context": "runs a search service with edge nodes", "use_case": "search indices across edge nodes", "switched_from": "", "story": "Ask HN: What Are You Working On? (July 2026)"}, {"id": 782227250, "item_id": 48889203, "url": "https://news.ycombinator.com/item?id=48889203", "by": "probst", "date": "2026-07-13", "stance": "neutral", "quote": "We used Meilisearch as the search backend in the beginning but have since replaced it", "excerpt": "We are working on our two site-search search engines Monocle Search [0] and SearchCue [1]. The former is squarely aimed at people using Squarespace, whereas our newer offering SearchCue is aimed at anyone with a site that wants to add search. We used Meilisearch as the search backend in the beginning but have since replaced it with a quite sophisticated search stack built around Tantivy [2]. We now support crawling a", "context": "", "use_case": "search backend", "switched_from": "", "story": "Ask HN: What Are You Working On? (July 2026)"}, {"id": 754549153, "item_id": 47159322, "url": "https://news.ycombinator.com/item?id=47159322", "by": "westurner", "date": "2026-02-25", "stance": "recommend", "quote": "MeiliSearch can be used as a vector database for langchain.", "excerpt": "Np. Still learning about how to reference agentskills from my coding LLM here. Haven't yet worked with MCP or A2A much. I should port instruction prompts from each project's AGENTS.md to reusable skills in .claude/skills/skillname/SKILL.md ; so that I can reference \"/skillname\" in a prompt to reuse that prompt text. Copilot looks for agent skills in .claude/skills/, .github/skills/, or .agents/skills/ . FWIU there ar", "context": "", "use_case": "search and vector database", "switched_from": "", "story": "Show HN: Saga \u2013 A Jira-like project tracker MCP server for AI agents (SQLite)"}, {"id": 733471344, "item_id": 45841959, "url": "https://news.ycombinator.com/item?id=45841959", "by": "costco", "date": "2025-11-06", "stance": "neutral", "quote": "My Meilisearch index is ~40GB", "excerpt": "I use a Hetzner server with Ryzen 7 3700X and an SSD. I think I could get the model to work with ONNX web but it'd be a 2GB download so the user experience wouldn't be too great. My Meilisearch index is ~40GB but I don't know how much that could be compressed down. Here's how the similar page for books is generated, which I forgot to mention on the \"how it works\" page: https://gist.github.com/chris124567/8d06d64bfe82", "context": "", "use_case": "search index for recommendation site", "switched_from": "", "story": "Show HN: I scraped 3B Goodreads reviews to train a better recommendation model"}]}