lucene
Typesense
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lucene | Typesense | |
---|---|---|
11 | 129 | |
2,344 | 17,876 | |
4.0% | 4.4% | |
9.8 | 9.8 | |
7 days ago | 6 days ago | |
Java | C++ | |
Apache License 2.0 | GNU General Public License v3.0 only |
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.
lucene
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Building an efficient sparse keyword index in Python
First, a review of the landscape. As said in the introduction, there aren't a ton of good options. Apache Lucene is by far the best traditional search index from a speed, performance and functionality standpoint. It's the base for Elasticsearch/OpenSearch and many other projects. But it requires Java.
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Java Panama Vector API Integrated with Apache Lucene
https://github.com/apache/lucene/issues/10047
2. The Panama Vector API allows CPU's that support it to accelerate vector operations: https://openjdk.org/jeps/438
So this allows fast ANN on Lucene for semantic search!
How did people do this before Lucene supported it? Only through entirely different tools?
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What Is a Vector Database
Are they forking Lucene or somehow getting the Lucene devs to increase that limit? Because this PR has been open for over a year now: https://github.com/apache/lucene/issues/11507
- An alternative to Elasticsearch that runs on a few MBs of RAM
- Lucene 9.4 (optionally) uses Panama's mapped MemorySegments when JDK 19 is detected
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A primer on Roaring bitmaps: what they are and how they work
Lucene's adaptation of Roaring uses the complement idea on a block-wise basis:
https://github.com/apache/lucene/blob/84cae4f27cfd3feb3bb42d...
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How are documents stored in Elasticsearch?
Like someone said, it's in locations as specified in the path.data. Depending on sharing and replication, it could be on more than one host. Elastic uses Apache Lucene to store documents, since it's open source, that rabbit hole will welcome research :-)
- panama/foreign status update
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Amazon Elasticsearch Service Is Now Amazon OpenSearch Service
It is pretty clear to me that Elastic is planning to build their ANN features differently than OpenDistro's k-NN implementation, or other plugins modules that extend Easticsearch in similar ways. They now will build on the Apache Lucene capabilities that were collaboratively built "upstream" by a number of individuals, some that work for Amazon and some that work for Elastic.
From the linked issue, it seemed that they were originally planning to develop this as a proprietary feature of Elasticsearch, without contributing the functionality to Apache Lucene, but then changed direction when the Apache Lucene developers (some of which are currently employed to do such work by Amazon) started to build its approximate nearest neighbor (ANN) vector search capabilities. [1]
It's great to see folks that work for Elastic collaborating and building on what is in Apache Lucene to extend the utility of ANN with Hierarchical Navigable Small World Graphs (HNSW) [2]! From this, I think it should be possible to implement an Open Source version of the functionality with a compatible API, if that is something that OpenSearch users seek.
[1] https://issues.apache.org/jira/browse/LUCENE-9004
[2] https://github.com/apache/lucene/pull/250
Typesense
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Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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DNS record "hn.algolia.com" is gone
If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.
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Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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Obsidian Publish full text search
I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.
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DynamoDB search options
A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
What are some alternatives?
pisa - PISA: Performant Indexes and Search for Academia
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
RoaringBitmap - A better compressed bitset in Java: used by Apache Spark, Netflix Atlas, Apache Pinot, Tablesaw, and many others
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
OpenSearch - 🔎 Open source distributed and RESTful search engine.
Apache Solr - Apache Lucene and Solr open-source search software
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
resin - Vector space search engine. Available as a HTTP service or as an embedded library.
loki - Like Prometheus, but for logs.
liqe - Lightweight and performant Lucene-like parser, serializer and search engine.
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.