Back Back to Articles

Analyzing Database Trends Through 1.8 Million Hacker News Headlines

Analyzing Database Trends Through 1.8 Million Hacker News Headlines

How the analysis was done

I used camelAI with a ClickHouse database of every HN story to do all analysis. You can use it for free with no login here to explore the data interactively yourself.


18 years • 1.8 million headlines • 13 database engines

Hacker News is a real-time barometer of developer excitement. I mined every story title from February 2007 to June 2025 and asked three questions:

  • How has headline volume for each database changed over time?
  • Which engines are accelerating the fastest right now?
  • Which ones are losing steam?

1 · Raw popularity through time

The chart below shows monthly headline counts for the eight most-talked-about engines, plus DuckDB (small base, big growth).

Click on the individual database names to toggle their visibility. Double click to isolate a single database.

PostgreSQL’s curve is a near-monotonic climb; by 2020 it dwarfs every other line. MySQL dominates the pre-2012 era, then flat-lines. MongoDB peaks around 2013, then slips as SQL engines add JSON support. ClickHouse (2016) and DuckDB (2020) rocket up in the analytics renaissance. Redis & SQLite are steady, underscoring their “invisible infrastructure” roles.

2 · Who’s gaining the fastest?

I compared the last 12 months (Jul 2024 – Jun 2025) with the previous 12 months, then fit a linear regression over the last 36 months to capture trajectory.

Engine Headlines 2024-25 2023-24 YoY Δ % 3-yr slope (mentions / mo)
DuckDB 225 149 +50.7 % +0.44
ClickHouse 211 170 +24.1 % +0.39
Supabase 105 84 +25.0 % +0.12
PostgreSQL 1 229 1 315 −6.6 % +1.22
Snowflake 106 156 −32.1 % +0.01
Redis 180 236 −23.7 % +0.07
MySQL 164 185 −11.4 % +0.03
MongoDB 96 78 +23.1 % +0.03
DynamoDB 25 38 −34.2 % −0.08
BigQuery 20 35 −42.9 % −0.05
Redshift 10 18 −44.4 % −0.05
TimescaleDB 3 4 −25.0 % −0.01

DuckDB tops the growth chart: half of its lifetime headlines appeared this year. ClickHouse maintains double-digit gains on a larger base, buoyed by vector search & managed services. Supabase benefits from the “Firebase, but OSS” narrative. PostgreSQL’s YoY dip merely reflects an all-time-high 2023; its 3-yr slope (+1.22) is the steepest of all. Cloud-native SaaS engines (DynamoDB, BigQuery, Redshift) are down sharply in share of conversation.

3 · Engines in decline

Headline counts aren’t everything, but they do reveal mind-share:

Engine Peak year Peak headlines 2024-25 headlines % off peak
MongoDB 2013 242 96 −60 %
MySQL 2009 267 164 −39 %
DynamoDB 2019 59 25 −58 %
BigQuery 2020 62 20 −68 %
Redshift 2016 61 10 −84 %

Why? Maturity – less novelty, fewer “Show HN” launches. OSS competition – Postgres extensions + parquet/iceberg lakehouses replace single-purpose stores. Discussion shift – Cost, lock-in, and serverless topics often omit the product name.

Takeaways

  • Open‑source engines drive most new discussion.
  • Analytics‑focused stores (DuckDB, ClickHouse) gain as work moves from batch to interactive.
  • Slow, steady improvement (PostgreSQL) beats hype cycles.
  • Proprietary cloud databases draw fewer submissions over time.

Further analysis

Questions you can run next:

  • Which databases appear most in headlines containing "alternative to" or "replacing"?
  • What's the ratio of positive (launched, shipped) vs negative (outage, breach) headlines?
  • How do vector database mentions (Pinecone, Weaviate, Qdrant) compare to traditional databases?
  • Which lesser-known databases are on exponential growth curves?

Run any query on the same dataset here, no login required.

Miguel Salinas