June 25, 2026
Trend drama, now with crash gossip
Show HN: I made Google Trends for Hacker News by indexing 18 years of comments
HN gets its own Google Trends and commenters instantly turn it into a lovefest plus outage watch
TLDR: A Hacker News creator built a Google Trends-style tracker for 18 years of site comments, turning old conversations into a searchable popularity chart. Commenters loved the idea and the look, then immediately joked it got loved so hard it started timing out.
A Hacker News user just dropped a tool that basically lets people time-travel through 18 years of internet nerd chatter, and the crowd reaction was immediate: part admiration, part gleeful chaos. The project charts how often words, tools, and names have appeared across roughly 45 million Hacker News posts and comments, then lets you click through to the actual arguments, hype waves, and obsession spikes behind the graph. In plain English, it’s like a popularity tracker for what the tech crowd has been talking about for nearly two decades.
And the comments? Very into it. The mood swung hard toward instant praise, with people calling it “sick,” saying they “love it,” and complimenting the clean, easy look. One person was already poking around the “linux” trend like it was celebrity gossip data for programmers. The creator leaned into the fun of watching topics suddenly explode as “small burst[s] of activity,” which gave the whole thing a popcorn-worthy vibe: not just data, but drama preserved in chart form.
But because this is the internet, the real plot twist arrived fast: success may have broken it. A commenter posted a timeout error and bluntly declared “Hug of death,” the classic online badge of honor meaning too many curious people showed up at once. So yes, the tool won over the crowd—and then the crowd may have immediately body-slammed it with affection. Honestly? That only made the launch feel even more iconic.
Key Points
- •The project charts how often topics, tools, or people have been mentioned on Hacker News over 18 years of comments.
- •Users can overlay multiple search terms to compare how their popularity changes over time.
- •The charts are live date histograms built from 45 million posts and comments.
- •The system is built using Upstash Redis Search.
- •The interface also shows the underlying stories and comments behind each chart line, with filtering by term or author.