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Lucene was written for public search engine like Google, or DuckDuckGo (which is actually based on Lucene and Solr). Lucene and Lucene-like projects (Tantivy o
by tpayet 7y ago
Lucene was written for public search engine like Google, or DuckDuckGo (which is actually based on Lucene and Solr).
Lucene and Lucene-like projects (Tantivy or Bleve in Golang) are general-purpose search libraries. They can handle enormous datasets, and you can make very complex queries on them (compute the average age of people named Karl in a certain type of document for example).
These libraries are based on tf-idf (term frequency inverse document frequency) algorithm and manage quite poorly typos for example (unless you make the setup to index your documents differently to parse them correctly).
Toshi is like Elastic for Lucene, it provides sharding and JSON over HTTP api.
You can basically used Lucene and its derivatives for basically any search related project, but you may have to dive into how it works and understand concepts like tokenization or ngrams to tune it according to your needs.
On the other hand, MeiliSearch (and I guess Typesense, but I can not talk for them) focus a subset of what you could build with Lucene or Elastic.
It is a fully functionnal Restful API, made for instant search or search-as-you-type. The algorithms behind MeiliSearch are simply different: a inverse index, with a levensthein automaton to handle typos, then a bucket sort you can tune for the ranking of the returned documents.
The aim is to provide a easyer go-to solution to implement for customer-facing search.
You won't be able to make super complex queries on terabytes of data. We just make super fast and ultra relevant search for end-user.
TypeSense and MeiliSearch focus on the same usage, we choose Rust for performance, security and the modern ecosystem that will allow easier maintenance :D
- ddorian43 7y agoDuckDuckGo isn't based on lucene/solr but bing-api.
- tpayet 7y agomy bad, my informations could be outdated. based on http://highscalability.com/blog/2013/1/28/duckduckgo-architecture-1-million-deep-searches-a-day-and-gr.html http://highscalability.com/blog/2013/1/28/duckduckgo-archite...: The fat tail queries go against PostgreSQL and the long tail queries go against Solr. For shorter queries PostgreSQL takes precedence. Long tail fills in Instance Answers where nothing else catches. It seems that Bing is now a part of their sources indeed: https://help.duckduckgo.com/results/sources https://help.duckduckgo.com/results/sources
- deleted 7y ago[deleted]
- bmn__ 7y agoBoth are used. Source: Torsten Raudssus who works for DDG as developer liaison.
- ddorian43 7y agoYou saying they do websearch in lucene/solr ? How many TB do they have in solr ?
- fulmicoton 7y agotantivy main dev here. Just chiming in to confirm this is an accurate answer.
- KajMagnus 7y agoThanks @tpayet and @fulmicoton for the info :- ) @fulmicoton and @tpayet, I'm thinking then if I want both full text search, and also faceted search, then Tantivy can do that, but at this time, MeiliSearch (and Typesense) don't do that? ( When I look here: https://github.com/meilisearch/MeiliSearch https://github.com/meilisearch/MeiliSearch in the features list, I see no mentioning of faceted search. Whilst Tantivy does list faceted search as a feature: https://github.com/tantivy-search/tantivy https://github.com/tantivy-search/tantivy ) @tpayet, for a database like MeiliSearch, is faceted search typically always off-topic? Or you're thinking about adding faceted search, later on? (My use case is 1) full text search, 2) typo friendly, and with 3) e.g. "begin" matching also "began", "begun", and "run" also matching "running", and 4) in all lanugages, and 5) faceted-search restricted to tags and categories and user groups.)
- karterk 7y agoTypesense does support faceted search. Look for the `facet_by` example in this section: https://typesense.org/docs/0.11.1/api/#search-collection https://typesense.org/docs/0.11.1/api/#search-collection
- KajMagnus 7y agoThanks! Based on what I read about Typesense, I'm thinking this faceted search happens in-memory (so one would want ok much RAM)
- tpayet 7y agoYou are welcome. MeiliSearch does not offer faceted search yet. It is one of the key feature that we are still missing but we plan to work on it in the coming weeks. For your use case today, I suggest you use Typesense if it fits your needs ( they handle faceted search already ) or Tantivy or Toshi. To manage different languages, you should make one index per language. MeiliSearch and Tantivy handles kanjis! We will add faceted search in the coming weeks if you are not in a hurry :D
- Dowwie 7y agoHave you contrasted MeliSearch with Sonic?
- tpayet 7y agoYes :) Valerian Saliou, the maintainer of Sonic is a friend of us. He built Sonic mainly for his company (crisp.chat) and compared to MeiliSearch there is no relevancy ranking. Sonic is "just" a inverted index with a levenshtein automaton, it will returns only the documents ids in which there is your requests words and then you will have to retrieve the full documents in your main database and only then can you apply some relevancy ranking by yourself.