Time Series Data in Redis: How We Search 18 Years of Hacker News in Milliseconds

The project hackernewstrends.com functions like Google Trends for Hacker News by analyzing the frequency of terms mentioned over time. It operates on a single Upstash Redis database that holds 45 million posts and comments, using Redis's unique data structures such as sorted sets, streams, and the RedisTimeSeries module for efficient time series data handling. The platform employs Redis Search to store each data point as a searchable document, allowing for full-text and date-based queries to generate trend lines. This method offers significant speed advantages over traditional approaches by conducting matching and bucketing operations directly on the Redis side, avoiding extensive client-side processing. The project emphasizes exact matching, a custom scoring function, and caching to maintain fast query responses, and is available as open-source code on GitHub, with live trials accessible at hackernewstrends.com.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.