bleve
zincsearch
bleve | zincsearch | |
---|---|---|
13 | 37 | |
9,674 | 16,523 | |
0.7% | 1.2% | |
8.0 | 6.6 | |
about 21 hours ago | 6 days ago | |
Go | 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.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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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
zincsearch
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OpenObserve: Elasticsearch/Datadog alternative in Rust.. 140x lower storage cost
Please give the benefit of the doubt on HN.
This company created ZincSearch:
https://github.com/zincsearch/zincsearch
Prabhat is one of the core contributors/maintainers:
https://github.com/zincsearch/zincsearch/graphs/contributors
https://github.com/prabhatsharma
Also the negative insinuation of using “cheap” labor out of India to build the product is unnecessary. If you’re concerned about code quality, look at the code.
Assuming everyone working with devs in India is doing so cynically is not charitable.
I dont know why the headquarters was set as india versus SF but does it actually even matter?
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Manticore 6.0.0 – a faster alternative to Elasticsearch in C++
See also this lightweight alternative to ES: https://github.com/zinclabs/zinc
- I created Atomic: Self Hosted Open Source Alternative to Reclaim, Clockwise & Motion
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Sonic: A Super-Light Alternative to Elasticsearch
I would pay $5 to have every one of these projects stop saying "alternative to ElasticSearch" unless they implement the ES API (as https://github.com/zinclabs/zinc at least claims) because if one just wanted some schemaless full text searching wizardry, there are about 10 of those projects. If one is trying to replace kibana or the damn near infinite log gathering tools that target ES, Sonic and Melisearch and and and are not going to get it done
q.v. https://github.com/zinclabs/zinc/blob/v0.3.6/docs/swagger.ya...
- Any Full Text Search library for json data?
- An alternative to Elasticsearch that runs on a few MBs of RAM
- ZincSearch – lightweight alternative to Elasticsearch written in Go
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Hacker News top posts: Sep 22, 2022
ZincSearch – lightweight alternative to Elasticsearch written in Go\ (0 comments)
What are some alternatives?
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
elastic - Deprecated: Use the official Elasticsearch client for Go at https://github.com/elastic/go-elasticsearch
goriak - goriak - Go language driver for Riak KV
dozzle - Realtime log viewer for docker containers.
elasticsql - convert sql to elasticsearch DSL in golang(go)
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
goes
quickwit - Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
elastigo - A Go (golang) based Elasticsearch client library.
quickwit - Quickwit is a fast and cost-efficient distributed search engine for large-scale, immutable data. [Moved to: https://github.com/quickwit-oss/quickwit]