rum VS pg_search

Compare rum vs pg_search and see what are their differences.

rum

RUM access method - inverted index with additional information in posting lists (by postgrespro)

pg_search

pg_search builds ActiveRecord named scopes that take advantage of PostgreSQL’s full text search (by Casecommons)
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rum pg_search
5 6
521 889
1.0% 1.7%
6.7 6.1
12 days ago 23 days ago
C Ruby
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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rum

Posts with mentions or reviews of rum. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-27.
  • Postgrespro/rum: RUM access method – inverted index with additional information
    1 project | news.ycombinator.com | 17 Dec 2021
  • Postgres Full-Text Search: A Search Engine in a Database
    10 projects | news.ycombinator.com | 27 Jul 2021
    My experience has been that sorting by relevance ranking is quite expensive. I looked into this a bit and found https://github.com/postgrespro/rum (and some earlier slide decks about it) that explains why the GIN index type can't support searching and ranking itself (meaning you need to do heap scans for ranking). This is especially problematic if your users routinely do searches that match a lot of documents and you only want to show the top X results.
    10 projects | news.ycombinator.com | 27 Jul 2021
    You might be just fine adding an unindexed tsvector column, since you've already filtered down the results.

    The GIN indexes for FTS don't really work in conjunction with other indices, which is why https://github.com/postgrespro/rum exists. Luckily, it sounds like you can use your existing indices to filter and let postgres scan for matches on the tsvector.

  • Debugging random slow writes in PostgreSQL
    1 project | news.ycombinator.com | 15 May 2021
    We have been bitten by the same behavior. I gave a talk with a friend about this exact topic (diagnosing GIN pending list updates) at PGCon 2019 in Ottawa[1][2].

    What you need to know is that the pending list will be merged with the main b-tree during several operations. Only one of them is so extremely critical for your insert performance - that is during actual insert. Both vacuum and autovacuum (including autovacuum analyze but not direct analyze) will merge the pending list. So frequent autovacuums are the first thing you should tune. Merging on insert happens when you exceed the gin_pending_list_limit. In all cases it is also interesting to know which memory parameter is used to rebuild the index as that inpacts how long it will take: work_mem (when triggered on insert), autovacuum_work_mem (when triggered during autovauum) and maintainance_work_mem (triggered by a call to gin_clean_pending_list()) define how much memory can be used for the rebuild.

    What you can do is:

    - tune the size of the pending list (like you did)

    - make sure vacuum runs frequently

    - if you have a bulk insert heavy workload (ie. nightly imports), drop the index and create it after inserting rows (not always makes sense business wise, depends on your app)

    - disable fastupdate, you pay a higher cost per insert but remove the fluctuctuation when the merge needs to happen

    The first thing was done in the article. However I believe the author still relies on the list being merged on insert. If vacuums were tuned agressively along with the limit (vacuums can be tuned per table). Then the list would be merged out of bound of ongoing inserts.

    I also had the pleasure of speaking with one main authors of GIN indexes (Oleg Bartunov) during the mentioned PGCon. He gave probably the best solution and informed me to "just use RUM indexes". RUM[3] indexes are like GIN indexes, without the pending list and with faster ranking, faster phrase searches and faster timestamp based ordering. It is however out of the main postgresql release so it might be hard to get it running if you don't control the extensions that are loaded to your Postgres instance.

    [1] - wideo https://www.youtube.com/watch?v=Brt41xnMZqo&t=1s

    [2] - slides https://www.pgcon.org/2019/schedule/attachments/541_Let's%20...

    [3] - https://github.com/postgrespro/rum

  • Show HN: Full text search Project Gutenberg (60m paragraphs)
    5 projects | news.ycombinator.com | 24 Jan 2021
    I suggest to have a look at https://github.com/postgrespro/rum if you haven’t yet. It solves the issue of slow ranking in PostgreSQL FTS.

pg_search

Posts with mentions or reviews of pg_search. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-15.
  • Application Search Feature more that ActiveRecord;
    2 projects | reddit.com/r/rails | 15 May 2022
    You can take a look at pg_search if you’re using Postgres
  • How to build a search engine with Ruby on Rails
    1 project | reddit.com/r/ruby | 11 Sep 2021
    This was a really good read, thanks. I've got into the habit of jumping straight to PgSearch but could definitely apply this approach to some existing projects.
  • Instant search with Rails 6 and Hotwire
    5 projects | dev.to | 6 Aug 2021
    Cleaner, more performant database queries: Definitely don't just leave your query sitting in the controller! For production use cases, you'd want to consider an option like pg_search
  • Postgres Full-Text Search: A Search Engine in a Database
    10 projects | news.ycombinator.com | 27 Jul 2021
    If you are using Rails with Postgres you can use pg_search gem to build the named scopes to take advantage of full text search.

    https://github.com/Casecommons/pg_search

  • Tips for optimizing pg_search?
    2 projects | reddit.com/r/rails | 14 Apr 2021
    Hey guys. Looking to release an app for mobile that will be using a rails API. The app will heavily rely on search. I know the go-to is to use elasticsearch but wanted to see if there was enough user demand for the MVP before shelling out $50/mo for the heroku add on. In the mean time I've been using pg_search. From the eye test it's performing okay but will be adding a table that houses over 350K records. With this in mind I was wondering if you all had any tips for increasing the overall speed for search from the model and controller level. Also should note that I'm open to any other free search gems if they deem bette fit.
  • Rails Search Bar
    2 projects | dev.to | 18 Oct 2020
    There are two basic search configurations with pg_search, a Single Model search scope or a multi Model configuration. In my case I am only using the Single Model configuration, but you can read more about multi-search in the documentation.

What are some alternatives?

When comparing rum and pg_search you can also consider the following projects:

ransack - Object-based searching.

Elasticsearch Rails - Elasticsearch integrations for ActiveModel/Record and Ruby on Rails

elasticsearch-ruby - Ruby integrations for Elasticsearch

textacular - Textacular exposes full text search capabilities from PostgreSQL, and allows you to declare full text indexes. Textacular will extend ActiveRecord with named_scope methods making searching easy and fun!

Searchkick - Intelligent search made easy

zombodb - Making Postgres and Elasticsearch work together like it's 2022

MeiliSearch - An open-source, lightning-fast, and hyper-relevant search engine that fits effortlessly into your apps, websites, and workflow.

Thinking Sphinx - Sphinx/Manticore plugin for ActiveRecord/Rails

Sunspot - Solr-powered search for Ruby objects

SearchCop - Search engine like fulltext query support for ActiveRecord

has_scope - Map incoming controller parameters to named scopes in your resources

pgsync - Sync data from one Postgres database to another