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Rum Alternatives
Similar projects and alternatives to rum
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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ripgrep
ripgrep recursively searches directories for a regex pattern while respecting your gitignore
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MeiliSearch
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
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Typesense
Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
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quickwit
Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
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SaaSHub
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sonic
🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
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tatoeba2
Tatoeba is a platform whose purpose is to create a collaborative and open dataset of sentences and their translations.
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pgx
Discontinued Build Postgres Extensions with Rust! [Moved to: https://github.com/tcdi/pgrx] (by tcdi)
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ora2pg
Ora2Pg is a free tool used to migrate an Oracle database to a PostgreSQL compatible schema. It connects your Oracle database, scan it automatically and extracts its structure or data, it then generates SQL scripts that you can load into PostgreSQL.
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pg_cjk_parser
Postgres CJK Parser pg_cjk_parser is a fts (full text search) parser derived from the default parser in PostgreSQL 11. When a postgres database uses utf-8 encoding, this parser supports all the features of the default parser while splitting CJK (Chinese, Japanese, Korean) characters into 2-gram tokens. If the database's encoding is not utf-8, the parser behaves just like the default parser.
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rum discussion
rum reviews and mentions
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Code Search Is Hard
the rum index has worked well for us on roughly 1TB of pdfs. written by postgrespro, same folks who wrote core text search and json indexing. not sure why rum not in core. we have no problems.
https://github.com/postgrespro/rum
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
If you need ranking, and you have the possibility to install PostgreSQL extensions, then you can consider an extension providing RUM indexes: https://github.com/postgrespro/rum. Otherwise, you'll have to use an "external" FTS engine like ElasticSearch.
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Features I'd Like in PostgreSQL
>Reduce the memory usage of prepared queries
Yes query plan reuse like every other db, this still blows me away PG replans every time unless you explicitly prepare and that's still per connection.
Better full-text scoring is one for me that's missing in that list, TF/IDF or BM25 please see: https://github.com/postgrespro/rum
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Ask HN: Books about full text search
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.
https://github.com/postgrespro/rum
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Postgres Full Text Search vs. the Rest
My experience with Postgres FTS (did a comparison with Elastic a couple years back), is that filtering works fine and is speedy enough, but ranking crumbles when the resulting set is large.
If you have a large-ish data set with lots of similar data (4M addresses and location names was the test case), Postgres FTS just doesn't perform.
There is no index that helps scoring results. You would have to install an extension like RUM index (https://github.com/postgrespro/rum) to improve this, which may or may not be an option (often not if you use managed databases).
If you want a best of both worlds, one could investigate this extensions (again, often not an option for managed databases): https://github.com/matthewfranglen/postgres-elasticsearch-fd...
Either way, writing something that indexes your postgres database into elastic/opensearch is a one time investment that usually pays off in the long run.
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Postgres Full-Text Search: A Search Engine in a Database
Mandatory mention of the RUM extension (https://github.com/postgrespro/rum) if this caught your eye. Lots of tutorials and conference presentations out there showcasing the advantages in terms of ranking, timestamps...
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.
- Postgrespro/rum: RUM access method – inverted index with additional information
- Debugging random slow writes in PostgreSQL
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Show HN: Full text search Project Gutenberg (60m paragraphs)
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.
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Stats
postgrespro/rum is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of rum is C.