autofaiss
Weaviate
| autofaiss | Weaviate | |
|---|---|---|
| 3 | 76 | |
| 748 | 9,524 | |
| 1.7% | 3.0% | |
| 5.6 | 10.0 | |
| 7 days ago | 7 days ago | |
| Python | Go | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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autofaiss
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You Don't Need LangChain;
I might be wrong here. I just know some product quantization techniques, but you can reduce the index by a lot! However, from my research, the more size you reduce, the more retrieval quality is also reduced.
Quoting from https://github.com/criteo/autofaiss
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Cheapest Vector Database
Autofaiss - https://github.com/criteo/autofaiss can be configured to make extremely tiny and efficient indexes.
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Vector database built for scalable similarity search
Don't start with mullivus if you're learning. Too much yak shaving. Try https://github.com/criteo/autofaiss.
Also, TBH, it is a lot cheaper to run a simple faiss index.
Weaviate
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
- FLaNK Stack 29 Jan 2024
- Qdrant, the Vector Search Database, raised $28M in a Series A round
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How to use Weaviate to store and query vector embeddings
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.
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Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
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Who's hiring developer advocates? (October 2023)
Link to GitHub -->
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Do we think about vector dbs wrong?
Hey @rvrs, I work on Weaviate and we are doing some improvements around increasing write throughput:
1. gRPC. Using gRPC to write vectors has had a really nice performance boost. It is released in Weaviate core but here is still some work on do on the clients. Feel free to get in contact if you would like to try it out.
2. Parameter tuning. lowering `efConstruction` can speed up imports.
3. We are also working on async indexing https://github.com/weaviate/weaviate/issues/3463 which will further speed things up.
In comparison with pgvector, Weaviate has more flexible query options such as hybrid search and quantization to save memory on larger datasets.
- Weaviate vector database
- Weaviate 1.21: Support for ImageBind and GPT4all and more
- Weaviate Vector Database
What are some alternatives?
vespa - AI + Data, online. https://vespa.ai
Milvus - A cloud-native vector database, storage for next generation AI applications
sqlite-vss - A SQLite extension for efficient vector search, based on Faiss!
faiss - A library for efficient similarity search and clustering of dense vectors.
milvus-lite - A lightweight version of Milvus wrapped with Python.
pgvector - Open-source vector similarity search for Postgres
typesense-instantsearch-semantic-search-demo - A demo that shows how to build a semantic search experience with Typesense's vector search feature and Instantsearch.js
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
jina - ☁️ Build multimodal AI applications with cloud-native stack
vald - Vald. A Highly Scalable Distributed Vector Search Engine