Searchkick
tantivy
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Searchkick | tantivy | |
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10 | 48 | |
6,389 | 9,839 | |
- | 3.3% | |
7.3 | 9.1 | |
15 days ago | 7 days ago | |
Ruby | Rust | |
MIT License | MIT License |
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.
Searchkick
- Searchkick: Intelligent Search Made Easy
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Most performant way to build an analytics dashboard from a relational database backend that only stores numeric values, where the data the end-user sees is "categorized" into numeric brackets (e.g. 60-79 = Med, 80-100 = High, etc)
I run a large scale production application that does something along these lines. If the data needs to be close to real-time, I'd say use `searchkick` + Elasticsearch, and use `searchkick`'s async feature to "stream" the data from your table to the ES index. Your dashboard will then just query from the ES index via searchkick.
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Postgres Full Text Search vs. the Rest
You're right, that's actually what we implemented, application-level hooks, but they needed development and maintenance effort that come for free with the adapter we're using for OpenSearch integration, which also comes with welcome features: synonyms, partial matches, and many others.
Spoiler, the adapter is Searchkick: https://github.com/ankane/searchkick
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Full-text Search with Elasticsearch in Rails
Searchkick
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How does elasticsearch work with a rails app that's already connected to a MySQL database.
Normally for Rails applications you would use a gem like searchkick since it greatly reduces the initial Elasticsearch complexity.
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Building a Workflow for Async Searchkick Reindexing
We lean heavily on Elasticsearch at CompanyCam. One of it's primary use cases is serving our highly filterable project feed. It is incredibly fast, even when you apply multiple filters to your query and are searching a largish data set. Our primary interface for interacting with Elasticsearch is using the Searchkick gem. Searchkick is a powerhouse and provides so many features out of the box. One place where we bump up against the edges is when trying to reindex a large collection.
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Swapping Elasticsearch for Meilisearch in Rails feat. Docker
Convinced? Ok read on and I’ll show you what switching from Elasticsearch to Meilisearch looked like for a real production app — ScribeHub. We also moved from Ankane’s excellent Searchkick gem to the first party meilisearch-rails gem and I’ll show you the changes there as well.
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Searching/Querying with Active Record Encryption
If you want to use a look-aside pattern (like you might have used with Searchkick + Elasticsearch), you should check out ActiveStash: https://github.com/cipherstash/activestash
- Full Text Searching in a MySQL database via rails.
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ransack VS Searchkick - a user suggested alternative
2 projects | 12 Aug 2021
Searchkick learns what your users are looking for. As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users. BONUS: it's written and supported by "ankane" who has flawless reputation amongst the Ruby community.
tantivy
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SeekStorm VS tantivy - a user suggested alternative
2 projects | 22 Mar 2024
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What is Hybrid Search?
Tantivy - a full-text indexing library written in Rust. Has a great performance and featureset.
- Tantivy – Fast, OSS full-text search library in Rust
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RAG Using Unstructured Data and Role of Knowledge Graphs
By this I presume you mean build a search index that can retrieve results based on keywords? I know certain databases use Lucene to build a keyword-based index on top of unstructured blobs of data. Another alternative is to use Tantivy (https://github.com/quickwit-oss/tantivy), a Rust version of Lucene, if building search indices via Java isn't your cup of tea :)
Both libraries offer multilingual support for keywords, I believe, so that's a benefit to vector search where multilingual embedding models are rather expensive.
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Show HN: Quickwit – OSS Alternative to Elasticsearch, Splunk, Datadog
We also implemented our schemaless columnar storage optimized for object storage.
The inverted index and columnar storage are part of tantivy [0], which is the fastest search library out there. We maintain it and we decided to build the distributed engine on top of it.
[0] tantivy github repo: https://github.com/quickwit-oss/tantivy
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Pg_bm25: Elastic-Quality Full Text Search Inside Postgres
The issue for geo search is here: https://github.com/quickwit-oss/tantivy/issues/44
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Grimoire - A recipe management application.
Search index : Custom-built using tantivy.
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A Compressed Indexable Bitset
The roaring bitmap variant is used only for the optional index (1 docid => 0 or 1 value) in the columnar storage (DocValues), not for the inverted index. Since this is used for aggregation, some queries may be a full scan.
The inverted index in tantivy uses bitpacked values of 128 elements with a skip index on top.
> I didn't follow the rest of your comment, select is what EF is good at, every other data structure needs a lot more scanning once you land on the right chunk. With BMI2 you can also use the PDEP instruction to accelerate the final select on a 64-bit block
The select for the sparse codec is a [simple array index access](https://github.com/quickwit-oss/tantivy/blob/main/columnar/s...), that is hard to beat. Compression is not good near the 5k threshold though.
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Job: Rust + Retrieval Systems at Etsy
Hi /r/rust, I’m a SWE on Etsy’s Retrieval Systems team where we’re building a platform based on rust and tantivy (https://github.com/quickwit-oss/tantivy). We’re looking to bring two new engineers onto the team.
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Announcing Velo - Your Rust-Powered Brainstorming and Note-Taking Tool
Quick Search: Easily find specific notes with Velo's fuzzy-search feature, powered by tantivy. tantivy might have been a little overkill, but it was really easy to integrate.
What are some alternatives?
chewy - High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
Elasticsearch Rails - Elasticsearch integrations for ActiveModel/Record and Ruby on Rails
surrealdb - A scalable, distributed, collaborative, document-graph database, for the realtime web
ransack - Object-based searching.
milli - Search engine library for Meilisearch ⚡️
pg_search - pg_search builds ActiveRecord named scopes that take advantage of PostgreSQL’s full text search
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
Sunspot - Solr-powered search for Ruby objects
quickwit - Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
elasticsearch-ruby - Ruby integrations for Elasticsearch
fselect - Find files with SQL-like queries