db-benchmarks VS charabia

> I decided to experiment with this setup and the NY Taxi Dataset. The initial goal was to populate ElasticSearch with ~14 million rows, loading data from a compressed parquet file of ~350 MB.

> I tried multiple times, but the operation failed continuously, due to JVM memory constraints

Here's a script https://github.com/db-benchmarks/db-benchmarks/blob/main/tes... which loads 1.7B NYC taxi ride documents into Elasticsearch.

In general, you are correct about another missing key: since we added an exception for MySQL by including two keys, we should perhaps optimize it to the maximum and add the rest as well. However, it would be better to make this more visible directly within the results then. I've created a task about it https://github.com/db-benchmarks/db-benchmarks/issues/30 . Thank you for pointing this out. If you see more issues, feel free to file them on github.

> It's interesting to note that Elasticsearch and Opensearch are general purpose search engine, Solr as well. They are all powered by Lucene, the popular and performant search engine library.

Another search engine which can be considered general, is not based on Lucene and is not less powerful than Elasticsearch/Solr is Manticore Search [1]

[1]: https://github.com/manticoresoftware/manticoresearch

> I would love to see some benchmarks by category :)

I'd love too. We started this work on db-benchmarks [2] , hopefully we'll have resources to continue it. Contributions are very welcome. It's 100% opensource [3]

[2]: https://db-benchmarks.com/

Comparing full-text search engines on queries that aren't full-text search are of course slow, these tests should be adapted to the proper usage of the tested DBs and not just benchmarked across the board..

Example: https://db-benchmarks.com/?cache=fast_avg&engines=elasticsea...

Clickhouse: no tuning , just CREATE TABLE ... ENGINE = MergeTree() ORDER BY id and standard clickhouse-server docker image.

MySQL and Percona Server for MySQL: no tuning , just CREATE TABLE ..., FULLTEXT(story_text,story_author,comment_text,comment_author))and standard mysql docker image .

https://db-benchmarks.com is a platform and a framework for making the most fair, transparent and open source database and search engines benchmarks. No more benchmarketing, because:

I hope to use this to submit a PR to meilisearch/charabia in the future based on the excellent example by benny-n in his pull request adding Hebrew support.

Good to know. If you find some Russian language support improvement we can do, don't hesitate to create an issue on our tokeniser https://github.com/meilisearch/charabia.

Moreover, it's Hacktoberfest. If you want to help us improve the language support, it would be awesome!

The Language support is mainly handled by the tokenizer where you can find specialized Segmenters and Normalizers that target some Language subtilities: https://github.com/meilisearch/charabia

Hi @tommoor

I work at Meilisearch so maybe a biased answer.

We do support other languages than English, it actually depends on what are the languages supported by our tokenizer https://github.com/meilisearch/charabia, so any language that uses whitespace to separate words(including English), Chinese, Japanese, Hebrew and Thai (Japaneze and Thai might work a little bit less)

Hello u/pkeep-go, at MeiliSearch we are implementing with the help of a contributor the CJK language support. We already have the Chinese support with Jieba but a contributor is adding the Korean and Japaneese support with Lindera. For us, it's really important to have people trying and helping us with languages we don't speak. If you want to make any contribution on the tokenization/language support part, we'll be happy to help!