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Life & fun · August 7, 2020

Hndex.org – a full-text search engine of articles submitted to HN

Hndex.org – a full-text search engine of articles submitted to HN launched on August 7, 2020 with 442 votes, #20 of 3,833 launches that month and more than 99% of that year's launches. The site was still online in September 2026, 6 years on.

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In plain words

Hndex.org is a full-text search engine that indexes articles submitted to Hacker News. Launched in 2020, it allows users to search through the body text of HN submissions rather than just titles and metadata. The tool is designed for Hacker News readers who want to find relevant articles from the site's history using keyword searches. It makes discovering past submissions and discussions more efficient by providing comprehensive text-based retrieval across the platform's content.

written from the facts on this page · September 2026

From the sources

hn dex was a site to search the full-text of articles submitted to Hacker News . It served as my test bed to play around with data structures and algorithms related to inverted indexes. I explored the problem through the lens of linear algebra and found some interesting ways to compress its sparse boolean matrices. The site used no JavaScript and aimed to serve a page of search results in under 100 μs on a $10/mo VPS. I'm retiring this project. I don't actually know if anyone is here (no logging ¯\_(ツ)_/¯ ). It's been a fun hobby and a great learning experience. Perhaps someday I'll write up a retrospective and share its story. Reach out via email or connect with me on GitHub to get in…from hndex.org

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    A discovery-focused search engine for Hacker News2024 · hn.trieve.ai · ▲193

    We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by…

  • hndex2020 · hndex.org · ▲1

    a search engine for finding articles posted to hacker news

  • Hacker Search – A semantic search engine for Hacker News2024 · hackersearch.net · ▲233

    Hi HN! I'm Jonathan and I built Hacker Search (https://hackersearch.net), a semantic search engine for Hacker News. Type a keyword or a description of what you're interested in, and you'll get top links from HN surfaced to you along with brief summaries. Unlike HN's otherwise very valuable search feature, Hacker Search doesn't require you to get your keywords exactly right. That's achieved by leveraging OpenAI's latest embedding models alongside more traditional indexes extracted from the scraped and cleaned up contents of the links. I think there are many more interesting things…

  • I made a search engine for Hacker News2024 · hackernews.demo.vectara.com · ▲211

    I love HN but always felt the search with algolia is okay but does have some limitations. Since I work at Vectara I decided to try and create a better search for HN. It's based on data from roughly the last 6 months of HN stories and comments. Would love to hear feedback and how useful this is relative to the existing search.

  • My recommendation engine for Hacker News2023 · hn-recommend.julienc.me · ▲314

    Hi! I’m Julien and I built a recommendation engine for Hacker News. I feel like this website is a gold mine. Every day, I find some very interesting stories about a topic. And sometimes, I want to find other stories covering that same topic but I can’t. Hacker News has years of history of awesome discussion and ressources. Unfortunately, I think HN Algolia isn’t helpful in searching these old threads. As a student, I want to learn a lot from this website. This is why I created HN Recommend. Input a sentence or the URL of an article, and get the most popular and similar posts from Hacker…

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