lucene
qdrant
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lucene | qdrant | |
---|---|---|
11 | 140 | |
2,358 | 17,839 | |
4.0% | 8.2% | |
9.8 | 9.9 | |
about 11 hours ago | 5 days ago | |
Java | Rust | |
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.
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
qdrant
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Boost Your Code's Efficiency: Introducing Semantic Cache with Qdrant
I took Qdrant for this project. The reason was that Qdrant stands for high-performance vector search, the best choice against use cases like finding similar function calls based on semantic similarity. Qdrant is not only powerful but also scalable to support a variety of advanced search features that are greatly useful to nuanced caching mechanisms like ours.
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Ask HN: Has Anyone Trained a personal LLM using their personal notes?
I'm currently looking to implement locally, using QDrant [1] for instance.
I'm just playing around, but it makes sense to have a runnable example for our users at work too :) [2].
[1]. https://qdrant.tech/
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Show HN: A fast HNSW implementation in Rust
Also compare with qdrant's Rust implementation; they tout their performance. https://github.com/qdrant/qdrant/tree/master/lib/segment/src...
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
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Open-source Rust-based RAG
There are much better known examples, such as https://qdrant.tech/ and https://github.com/lancedb/lancedb
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Qdrant 1.8.0 - Major Performance Enhancements
For more information, see our release notes. Qdrant is an open source project. We welcome your contributions; raise issues, or contribute via pull requests!
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Perform Image-Driven Reverse Image Search on E-Commerce Sites with ImageBind and Qdrant
Initialize the Qdrant Client with in-memory storage. The collection name will be “imagebind_data” and we will be using cosine distance.
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7 Vector Databases Every Developer Should Know!
Qdrant is an open-source vector search engine optimized for performance and flexibility. It supports both exact and approximate nearest neighbor search, providing a balance between accuracy and speed for various AI and ML applications.
- Ask HN: Who is hiring? (February 2024)
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Step-by-Step Guide to Building LLM Applications with Ruby (Using Langchain and Qdrant)
Qdrant serves as a vector database, optimized for handling high-dimensional data typically found in AI and ML applications. It's designed for efficient storage and retrieval of vectors, making it an ideal solution for managing the data produced and consumed by AI models like Mistral 7B. In our setup, Qdrant handles the storage of vectors generated by the language model, facilitating quick and accurate retrievals.
What are some alternatives?
pisa - PISA: Performant Indexes and Search for Academia
Milvus - A cloud-native vector database, storage for next generation AI applications
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
RoaringBitmap - A better compressed bitset in Java: used by Apache Spark, Netflix Atlas, Apache Pinot, Tablesaw, and many others
faiss - A library for efficient similarity search and clustering of dense vectors.
OpenSearch - 🔎 Open source distributed and RESTful search engine.
pgvector - Open-source vector similarity search for Postgres
Apache Solr - Apache Lucene and Solr open-source search software
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
resin - Vector space search engine. Available as a HTTP service or as an embedded library.
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.