Apache Solr VS MeiliSearch

There are already many project about search:

- https://www.marginalia.nu/

- https://searchmysite.net/

- https://lucene.apache.org/

- elastic search

- https://presearch.com/

- https://stract.com/

- https://wiby.me/

I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.

I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.

- domains for seed https://github.com/rumca-js/Internet-Places-Database

- bookmarks seed https://github.com/rumca-js/RSS-Link-Database

- links for year https://github.com/rumca-js/RSS-Link-Database-2024

Elasticsearch is based on Lucene and is used by various companies and developers across the world to build custom search solutions.

elastic search is kinda heavyweight infra for a small project. Its built on top of apache lucene (https://lucene.apache.org), which you can use directly.

Elasticsearch is based on Lucene, which is built in Java. This means that monitoring the Java Virtual Machine (JVM) memory is crucial to understand the current usage of the whole system.

Apache Lucene which seems to have a lot more features than Elasticsearch

Generally with term vectors and a tf-idf index. Lucene is a good starting place to help.

try elasticsearch or solr, behind the scenes they both use https://lucene.apache.org/ if you don't want basically a full nosql database service, but I'd just slap solr up and call it a day.

OpenSearch is an open-source database to ingest, search, visualize, and analyze data. It’s built on top of Apache Lucerce, a FOSS library for indexing and search, which OpenSearch leverages for more advanced analytics capabilities, like anomaly detection, machine learning, full-text search, and more.

Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust).

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.

Meilisearch

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.

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.

Meilisearch seems like it is the best open source option.

https://www.meilisearch.com/

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.

I work at Meilisearch, an open-source search engine built in Rust. 🦀

https://www.meilisearch.com/ https://github.com/meilisearch