solr
bleve
solr | bleve | |
---|---|---|
6 | 13 | |
1,015 | 9,674 | |
2.7% | 0.7% | |
9.8 | 8.0 | |
6 days ago | 2 days ago | |
Java | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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solr
- Iniciando no Elasticsearch: Conceitos básicos
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Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research.
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Looking for software
Apache Solr can be used to index and search text-based documents. It supports a wide range of file formats including PDFs, Microsoft Office documents, and plain text files. https://solr.apache.org/
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What do you use for site search? Custom built solution? Meilisearch? Algolia?
Solr https://solr.apache.org/
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'google-like' search engine for files on my NAS
if so, then https://solr.apache.org/ can be a solution, though there's a bit of setup involved. oh yea, you get to write your own "search interface" too which would end up calling solr's api to find stuff.
- An alternative to Elasticsearch that runs on a few MBs of RAM
bleve
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Hermes v1.7
I don't have the answer to that, but the project has been alive for many years. Seems maybe you should find the answer since you are developing a competing solution? Also it might be a good reference project for solving similar problems to yours. They do have bench tests you could play with https://github.com/blevesearch/bleve/blob/master/query_bench_test.go
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Seeking a free full text search solution for large data with progress display
I know of https://github.com/blevesearch/bleve and I think there was another project for full text search that I can't find now.
- Any Full Text Search library for json data?
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An alternative to Elasticsearch that runs on a few MBs of RAM
I would be interested in such a testbed. I would also like to know how Bleve Search (https://github.com/blevesearch/bleve) turns out.
I have for many years now a small search engine project in my free-time pipeline, but I'm before crawling even and I intend to sit for searching part after some of that.
- What is the coolest Go open source projects you have seen?
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BetterCache 2.0 (has full text search/remove, etc.)
Haha. Seriously I can’t tell the difference between these libraries https://github.com/blevesearch/bleve
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I want to dive into how to make search engines
I've never worked on a project that encompasses as many computer science algorithms as a search engine. There are a lot of topics you can lookup in "Information Storage and Retrieval":
- Tries (patricia, radix, etc...)
- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)
- Consensus (raft, paxos, etc..)
- Block storage (disk block size optimizations, mmap files, delta storage, etc..)
- Probabilistic filters (hyperloloog, bloom filters, etc...)
- Binary Search (sstables, sorted inverted indexes, roaring bitmaps)
- Ranking (pagerank, tf/idf, bm25, etc...)
- NLP (stemming, POS tagging, subject identification, sentiment analysis etc...)
- HTML (document parsing/lexing)
- Images (exif extraction, removal, resizing / proxying, etc...)
- Queues (SQS, NATS, Apollo, etc...)
- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)
- Rate limiting (leaky bucket, windowed, etc...)
- Compression
- Applied linear algebra
- Text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)
- etc...
I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.
- https://github.com/quickwit-oss/tantivy
- https://github.com/valeriansaliou/sonic
- https://github.com/mosuka/phalanx
- https://github.com/meilisearch/MeiliSearch
- https://github.com/blevesearch/bleve
- https://github.com/thomasjungblut/go-sstables
A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. The problem is that search with good rankings often requires custom storage so calculations can be sharded among multiple nodes and you can do layered ranking without passing huge blobs of results between systems.
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Why Writing Your Own Search Engine Is Hard (2004)
For those curious, I'm on my 3rd search engine as I keep discovering new methods of compactly and efficiently processing and querying results.
There isn't a one-size-fits all approach, but I've never worked on a project that encompasses as many computer science algorithms as a search engine.
- Tries (patricia, radix, etc...)
- Trees (b-trees, b+trees, merkle trees, log-structured merge-tree, etc..)
- Consensus (raft, paxos, etc..)
- Block storage (disk block size optimizations, mmap files, delta storage, etc..)
- Probabilistic filters (hyperloloog, bloom filters, etc...)
- Binary Search (sstables, sorted inverted indexes)
- Ranking (pagerank, tf/idf, bm25, etc...)
- NLP (stemming, POS tagging, subject identification, etc...)
- HTML (document parsing/lexing)
- Images (exif extraction, removal, resizing / proxying, etc...)
- Queues (SQS, NATS, Apollo, etc...)
- Clustering (k-means, density, hierarchical, gaussian distributions, etc...)
- Rate limiting (leaky bucket, windowed, etc...)
- text processing (unicode-normalization, slugify, sanitation, lossless and lossy hashing like metaphone and document fingerprinting)
- etc...
I'm sure there is plenty more I've missed. There are lots of generic structures involved like hashes, linked-lists, skip-lists, heaps and priority queues and this is just to get 2000's level basic tech.
- https://github.com/quickwit-oss/tantivy
- https://github.com/valeriansaliou/sonic
- https://github.com/mosuka/phalanx
- https://github.com/meilisearch/MeiliSearch
- https://github.com/blevesearch/bleve
A lot of people new to this space mistakenly think you can just throw elastic search or postgres fulltext search in front of terabytes of records and have something decent. That might work for something small like a curated collection of a few hundred sites.
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Mattermost – open-source platform for secure collaboration
Search in SQL databases is a tough beast to get it right. And given that we support MySQL and Postgres both, it gets even harder to support quirks of both of them.
In enterprise editions, the only addition is Elasticsearch. But in our open-source version, we do have support for https://github.com/blevesearch/bleve. Although, it's in beta, we have a lot of customers using it.
I am wondering if you have tried using it and didn't like it?
- A Database for 2022
What are some alternatives?
llm-integration - spring-starter, which enables semantic search, backed by OpenAI, by couple of lines
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
open-semantic-search - Open Source research tool to search, browse, analyze and explore large document collections by Semantic Search Engine and Open Source Text Mining & Text Analytics platform (Integrates ETL for document processing, OCR for images & PDF, named entity recognition for persons, organizations & locations, metadata management by thesaurus & ontologies, search user interface & search apps for fulltext search, faceted search & knowledge graph)
elastic - Deprecated: Use the official Elasticsearch client for Go at https://github.com/elastic/go-elasticsearch
fess - Fess is very powerful and easily deployable Enterprise Search Server.
goriak - goriak - Go language driver for Riak KV
swirl-search - Swirl is an open-source search platform that uses AI to search multiple content and data sources simultaneously and return AI-ranked results. And provides summaries of your answers from searches using LLMs. It's a one-click, easy-to-use Retrieval Augmented Generation (RAG) Solution.
elasticsql - convert sql to elasticsearch DSL in golang(go)
orange - Cross-platform local file search engine.
goes
LuceneBench - Lucene Benchmark : benchmarking Lucene vs. SeekStorm
elastigo - A Go (golang) based Elasticsearch client library.