MeiliSearch
Typesense
Our great sponsors
MeiliSearch | Typesense | |
---|---|---|
129 | 129 | |
42,538 | 17,425 | |
2.5% | 4.1% | |
9.8 | 9.8 | |
5 days ago | 6 days ago | |
Rust | 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.
MeiliSearch
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Publish/Subscribe with Sidekiq
We needed to introduce a new service for search. As we settled on using meilisearch, we needed a way to sync updates on our models with the records in meilisearch. We could've continued to use callbacks but we needed something better.
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The Mechanics of Silicon Valley Pump and Dump Schemes
Meilisearch
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What is Hybrid Search?
In this case, a good strategy is to use vector search only when the keyword/prefix search returns none or just a small number of results. A good candidate for this is MeiliSearch. It uses custom ranking rules to provide results as fast as the user can type.
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Create a ChatBot with VertexAI and LibreChat
With the VertexAI endpoint set up and tested, our next step is to work with LibreChat. LibreChat is an open-source ChatGPT clone that can integrate with various AI models, including the PaLM 2 models via the VertexAI API. It's built using React, MongoDB, and Meilisearch technologies.
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Pg_bm25: Elastic-Quality Full Text Search Inside Postgres
Meilisearch seems like it is the best open source option.
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Vector storage is coming to Meilisearch to empower search through AI
Starting with v1.3, you can use Meilisearch as a vector store. Meilisearch allows you to store vector embeddings alongside your documents conveniently. You will need to create the vector embeddings using your third-party tool of choice (Hugging Face, OpenAI). As we published the first v1.3 release candidate, you can try out vector search today.
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[N] Open-source search engine Meilisearch launches vector search
I work at Meilisearch, an open-source search engine built in Rust. š¦
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Creating search engine for your local network - Is it even possible?
https://www.meilisearch.com/ https://github.com/meilisearch
- Meilisearch across the Semantic Verse
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Docker file to allow serving/hosting of a directory of files via web browser
1) your program uses a db to index but the actual search is querying too much data at a time and you need to chop the server side query into smaller/faster queries. you could build your own efficient search with something like https://github.com/meilisearch/meilisearch
Typesense
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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
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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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.
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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
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
Iām also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
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Is elasticsearch for me? Currently using Full text search
Elasticsearch is heavy to run and manage. Take a look at Meilisearch and Typesense
- Awesome Self-hosted Search
What are some alternatives?
zincsearch - ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Searx - Privacy-respecting metasearch engine
sonic - š¦ Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
rust-postgres - Native PostgreSQL driver for the Rust programming language
Apache Solr - Apache Lucene and Solr open-source search software
OpenSearch - š Open source distributed and RESTful search engine.
quickwit - Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
Yacy - Distributed Peer-to-Peer Web Search Engine and Intranet Search Appliance
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
loki - Like Prometheus, but for logs.