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[Question]: Do you have plan to support other vector databases? #491

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shaoyie opened this issue Apr 22, 2024 · 7 comments
Open

[Question]: Do you have plan to support other vector databases? #491

shaoyie opened this issue Apr 22, 2024 · 7 comments
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@shaoyie
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shaoyie commented Apr 22, 2024

Describe your problem

Noticed now the backend is coupling with ElasticSearch.
Do you have plan to support some other vector stores, such as Pinecone, Milvus, etc.?

@shaoyie shaoyie added the question Further information is requested label Apr 22, 2024
@shaoyie shaoyie changed the title [Question]: Do you have plan to support other vector bases? [Question]: Do you have plan to support other vector databases? Apr 22, 2024
@KevinHuSh
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Do these support hybrid search like weighted vector similarity and keyword similarity?
I don't think they do.

@jlcbj
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jlcbj commented Apr 25, 2024

Milvus 2.4 support hybrid search

@KevinHuSh
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Milvus 2.4 support hybrid search

Can Milvus support text similarity calculation such as BM25 and TFIDF?

@Nuclear6
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I feel that the latest vector database is better than the currently used hybrid retrieval. Everyone has updated and iterated to the ANN algorithm, and the ragflow project is still using the KNN algorithm.

@nadirvishun
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I have tested the pgvector vector store of fastgpt and the weaviate vector store of dify, both using bce-embedding-base. The retrieval effects of both are better than the es vector store of ragflow, but I am not very sure if it is due to the vector store.

@taowang1993
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I have tested the pgvector vector store of fastgpt and the weaviate vector store of dify, both using bce-embedding-base. The retrieval effects of both are better than the es vector store of ragflow, but I am not very sure if it is due to the vector store.

how do you compare Dify vs Ragflow?

I am using Dify with Milvus to build a RAG application.

But I am not sure if ragflow is a better option than Dify.

seems like Dify is going to update to RAG2.0 at the end of this year.

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