SISigmundA·Sep 11, 2018
My understanding is gin/gist indexes do not store enough information to use better scoring and RUM indexes could change that:
https://github.com/postgrespro/rum
In PostgreSQL 11 and Just in Time Compilation of Queriespostgrespro
rum
C2016–2024
postgrespro / rum
rum
RUM access method - inverted index with additional information in posting lists
13Distinct people
33Mentions
1Explicit recommenders
849GitHub stars
What to know before exploring
What it is
RUM access method - inverted index with additional information in posting lists
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
for postgres, i highly recommend the rum index over the core fts. rum is written by postgrespro, who also wrote core fts and json indexing in pg.…
johnthescott used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 6:01:08 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year33 dated mentions
Observed mentions: 2016-10-02 14:16:46 UTC to 2024-08-07 01:25:25 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 6 | 0 | 6 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 7 | 1 | 6 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 2 | 0 | 2 |
What Hacker News says
3 sourcesthe biggest issue with postgres search is the inability to use TF-IDF or BM25 (the current default and state of the art on elasticsearch). The current ranking system is not very relevant.
Anyone who is familiar with PG internals - is there something in the internal data structure that prevents a BM25 or TF-IDF style rank generation ?
The work on RUM seems to have stagnated (and TF-IDF was a todo anyhow here) https://github.com/postgrespro/rum
I have a theory that if they incorporate these algorithms, it makes postgres potent enough that a lot of people may choose not to use elasticsearch/lucene.
In Setting Up a Fast, Comprehensive Search Routine with PostgreSQLThe upside: only one service to maintain (PostgreSQL) instead of two (PostgreSQL + ElasticSearch) and not having to synchronize PostgreSQL and ElasticSearch (which is more difficult than it sounds).
The downside: ranking can be slow when your keywords match a large number of documents (have a look at github.com/postgrespro/rum for a solution), and faceting is more difficult to implement than in ElasticSearch
In Setting Up a Fast, Comprehensive Search Routine with PostgreSQL