PostgreSQL full-text search
Shares rank 36 of 38 search engines by recommenders
Built into PostgreSQL at no extra cost, people recommend it for many search needs; the common caveat is that it lacks corpus-wide ranking like BM25.
Built into PostgreSQL at no extra cost, people recommend it for many search needs; the common caveat is that it lacks corpus-wide ranking like BM25.
12 people gave an opinion
- recommend it
- 5
- criticize it
- 7
- approval share
- 42%
Recommended in 4 of 13 months
- November 2025: not recommended
- December 2025: recommended
- January 2026: not recommended
- February 2026: not recommended
- March 2026: recommended
- April 2026: not recommended
- May 2026: not recommended
- June 2026: recommended
- July 2026: not recommended
- August 2026: not recommended
- September 2026: recommended
- October 2026: not recommended
- November 2026: not recommended (month in progress)
Why it doesn’t carry the badge
- 5 people recommend itNeeds 10 or more, not met.
- 0.7 recommenders for every criticNeeds 2 to 1 or better, not met.
- Recommended in 4 of 13 monthsNeeds 4 or more, met.
The same three rules apply to every product, and the badge can’t be bought. How the badge works
What people say about it
The reasons people give, with the number of comments that give each one. Open a reason to read what they said.
Why people recommend it
Each mark is one comment
Built into Postgres, long-established
“just use postrgres full text search”
Comment from 25 Jun 2026 in “Elastic lays off 7% of employees” “postgres has had FTS for decades”
Comment from 20 Sep 2026 in “Tin: full-text search for Postgres”
What people warn about
Each mark is one comment
No corpus-wide ranking like BM25
“it's missing an important feature: ranking based on the overall document collection”
Comment from 19 Sep 2026 in “Tin: full-text search for Postgres” “which works well but doesn't have whole-index ranking algorithms”
Comment from 31 Mar 2026 in “Show HN: How This Graybeard Built the Fastest and Freest Postgres BM25 Search” “The built in search can't do any scoring mechanism that involves corpus-wide stats”
Comment from 19 Sep 2026 in “Tin: full-text search for Postgres” - Comment from 17 Feb 2026 in “Hybrid Search in PostgreSQL: The Missing Manual”
Not enough for serious search
“It is wild to see people talk about Postgres fulltext like it’s all you could need, even for small apps.”
Comment from 21 Aug 2026 in “PostgreSQL for Everything” “you wouldn't want to use Postgres FTS”
Comment from 2 Oct 2026 in “RIP, vector database”
Other search engines people recommend
The four most recommended other search engines, with the same counts for each, so you can compare like for like. The tick on each bar marks the 2 to 1 line the badge needs.
| Product | Recommend | Criticize | Approval | Months | Owned | Badge |
|---|---|---|---|---|---|---|
| Kagi | 732 | 234 | 76% | 13 | 2 yrs106 owners | Approved |
| Google Search | 315 | 1,039 | 23% | 12 | 20 yrs25 owners | — |
| DuckDuckGo | 286 | 204 | 58% | 12 | 3.5 yrs47 owners | — |
| Hister | 81 | 9 | 90% | 9 | 2 mo17 owners | Approved |
| PostgreSQL full-text searchThis page | 5 | 7 | 42% | 4 | — | — |
What people said
12 of the 13 comments that mention it, newest first. Each links to the original comment.
“you wouldn't want to use Postgres FTS”
“postgres has had FTS for decades”
“it's missing an important feature: ranking based on the overall document collection”
“the Postgres built in one is missing many languages”
“The built in search can't do any scoring mechanism that involves corpus-wide stats”
“quite sophisticated full text search package integrated with functional indexing and query optimization”
“it is not capable of ordered index scan that handles both filtering”
“It is wild to see people talk about Postgres fulltext like it’s all you could need, even for small apps.”
“just use postrgres full text search”
“which works well but doesn't have whole-index ranking algorithms”
“it doesn't account for global term frequency like BM25 does”
“If you don't search so much for natural language, but more for specific keywords the stemming in fulltext search can get in the way.”
Counts come from 1,795,640 Hacker News comments, November 2025 to November 2026. How we count. Report a mistake.