postgres-elasticsearch-fdw
postgres-elasticsearch-fd
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postgres-elasticsearch-fdw | postgres-elasticsearch-fd | |
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3 | 3 | |
106 | - | |
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4.2 | - | |
28 days ago | - | |
Python | ||
MIT License | - |
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postgres-elasticsearch-fdw
- Full-text search engine with PostgreSQL (part 2): Postgres vs. Elasticsearch
-
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.
-
Lesser Known PostgreSQL Features
I used a foreign data wrapper to query elasticsearch indexes from within postgres.[0]
It pushed alot of complexity down away from higher-level app developers not familiar with ES patterns.
[0]: https://github.com/matthewfranglen/postgres-elasticsearch-fd...
postgres-elasticsearch-fd
- Full-text search engine with PostgreSQL (part 2): Postgres vs. Elasticsearch
-
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.
-
Lesser Known PostgreSQL Features
I used a foreign data wrapper to query elasticsearch indexes from within postgres.[0]
It pushed alot of complexity down away from higher-level app developers not familiar with ES patterns.
[0]: https://github.com/matthewfranglen/postgres-elasticsearch-fd...
What are some alternatives?
rum - RUM access method - inverted index with additional information in posting lists
zombodb - Making Postgres and Elasticsearch work together like it's 2023
tbls - tbls is a CI-Friendly tool for document a database, written in Go.
ksuid - K-Sortable Globally Unique IDs
pg-ulid - ULID Functions for PostgreSQL
tantivy - Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
pgvector - Open-source vector similarity search for Postgres
Searchkick - Intelligent search made easy
js-id - ID generation for JavaScript & TypeScript Applications
quickwit - Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.