vector-db-benchmark
vector-search
vector-db-benchmark | vector-search | |
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6 | 7 | |
227 | 247 | |
7.9% | - | |
9.1 | 3.2 | |
5 days ago | 10 months ago | |
Python | Jupyter Notebook | |
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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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.
vector-db-benchmark
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RAG is Dead. Long Live RAG!
Qdrant’s benchmark results are strongly in favor of accuracy and efficiency. We recommend that you consider them before deciding that an LLM is enough. Take a look at our open-source benchmark reports and try out the tests yourself.
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Evaluate Vector Database / Benchmarks?
Qdrant made their own benchmark. It is quite simple and also takes into consideration more options, so it should be better suited for benchmarking for production purposes.
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Qdrant, Pinecone, Supabase
is noWhen it comes to Supabase, it's using pgvector under the hood, so it would make sense to benchmark it with the other Open Source tools. There is an open PR for that, but it's pretty old: https://github.com/qdrant/vector-db-benchmark/pull/50
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Building a Vector Database with Rust to Make Use of Vector Embeddings
P.S.: Perhaps you want to add your database to our benchmarks repo?
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New and Improved Embedding Model for OpenAI
Do we have any idea why lucene vector search underperforms? As of lucene 9.1 (and elastic 8.4), it runs the same sort of filtered/categorical HNSW that qdrant runs (https://lucene.apache.org/core/9_1_0/core/org/apache/lucene/...). Qdrant's benchmarking code (https://github.com/qdrant/vector-db-benchmark/blob/9263ba/en...) does use the new filtered ann query with elastic 8.4, so it appears to be a fair benchmark. Why is lucene/elastic so much slower? Is it a rust vs. java thing? Or some memory management issues?
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Which vector search engine is the fastest?
There is also an open-source framework for benchmarking https://github.com/qdrant/vector-db-benchmark
vector-search
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Evaluate Vector Database / Benchmarks?
i started doing this at http://vectorsearch.dev but it could use some love.
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It’s the best time to travel with recurring income using A.I. anybody want help?
this isn't keyword search it's vector search. learn more here: https://vectorsearch.dev/
- Show HN: Vector Search Engine 101
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Ask HN: Books about full text search
series of tutorials and comparisons that aim to teach a foundations about vector search: https://vectorsearch.dev/
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How do I train a model to score sentences? (i.e. with BERT)
sounds like how vector search engines work, you convert a corpus into embeddings then search and the results are ordered by relevance score. i’m building a series of tutorials here: http://vectorsearch.dev
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Algolia Acquires Search.io
working on a comparison table: https://github.com/esteininger/vector-search/tree/master/fou...
What are some alternatives?
citrus - (distributed) vector database
relevanceai - Home of the AI workforce - Multi-agent system, AI agents & tools
ann-benchmarks - Benchmarks of approximate nearest neighbor libraries in Python
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
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
nimsearch - A nascent tutorial/intro to search engine ideas in Nim
weaviate-examples - Weaviate vector database – examples
SearchGar - SearchGar - An actual Search Engine made using Python
instant-distance - Fast approximate nearest neighbor searching in Rust, based on HNSW index
hora - 🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
rum - RUM access method - inverted index with additional information in posting lists