postgres-elasticsearch-fdw
Typesense
Our great sponsors
postgres-elasticsearch-fdw | Typesense | |
---|---|---|
3 | 129 | |
106 | 17,965 | |
- | 4.8% | |
4.2 | 9.8 | |
29 days ago | 3 days ago | |
Python | C++ | |
MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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...
Typesense
-
Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
-
Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
-
DNS record "hn.algolia.com" is gone
If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.
-
Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
-
Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
-
Obsidian Publish full text search
I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.
-
DynamoDB search options
A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.
-
[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
-
Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
What are some alternatives?
rum - RUM access method - inverted index with additional information in posting lists
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
tbls - tbls is a CI-Friendly tool for document a database, written in Go.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
pg-ulid - ULID Functions for PostgreSQL
Apache Solr - Apache Lucene and Solr open-source search software
pgvector - Open-source vector similarity search for Postgres
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
postgres-elasticsearch-fd
loki - Like Prometheus, but for logs.
js-id - ID generation for JavaScript & TypeScript Applications
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.