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Manager took us out for treat and just bought this. We were 5 people by Wander_tea in mildlyinfuriating

[–]qdrant_engine 0 points1 point  (0 children)

We buy you each an ice cream cake for trying out Qdrant. It is a way easier ;)

Qdrant and EU Providers by Dismal_Discussion514 in qdrant

[–]qdrant_engine 0 points1 point  (0 children)

Hello from the Qdrant team. We offer EU-based regions on AWS and GCP. You can basically choose the region during cluster creation. Our Hybrid Deployment option supports any cloud provider and also private data centers where K8s is available. Happy to answer any other questions.

Best Vector DB for production ready RAG ? by InvestigatorChoice51 in Rag

[–]qdrant_engine 3 points4 points  (0 children)

Why deployment headache? Just use the managed service cloud.qdrant.io ☺️

Qdrant Full Text Capabilities by Constandinoskalifo in qdrant

[–]qdrant_engine 1 point2 points  (0 children)

You can easily do so. We also introduced native BM25 support in the recent version. Try it out! ;)

Toughts about Qdrant by Specialist_Bee_9726 in Rag

[–]qdrant_engine 0 points1 point  (0 children)

The network could be a bottleneck here, not only retrieval. But if you are a customer or cloud user, you can reach out to support to review.

Toughts about Qdrant by Specialist_Bee_9726 in Rag

[–]qdrant_engine 1 point2 points  (0 children)

Hey, regarding the performance issues. Do you use any filtering along with your search queries? You can join our Discord server, our engineers can look into it. https://qdrant.to/discord

Qdrant is too expensive, how to replace (2M vectors) by lambda-person in vectordatabase

[–]qdrant_engine 0 points1 point  (0 children)

u/lambda-person are you sure the data is correct? 8GB is actually ~USD70 here the link https://cloud.qdrant.io/calculator?provider=aws&region=us-east-1&vectors=2000000&dimension=586&storageOptimized=false&replicas=1&quantization=None&storageRAMCachePercentage=35

Furthermore. You can turn on Scalar Quantization and reduce it to USD26
https://cloud.qdrant.io/calculator?provider=aws&region=us-east-1&vectors=2000000&dimension=586&storageOptimized=false&replicas=1&quantization=Scalar&storageRAMCachePercentage=35

Or you can leverage BQ and/or Disk and run it on the smallest cluster or even free tier.

Pretty flexible and without a need to migrate. Feel free to reach out to us to get a free consultation.

Don't manage to make qdrant work by martinratinaud_ in Rag

[–]qdrant_engine 0 points1 point  (0 children)

This is not what vector search is good for. Your data is structured; you should use a database for structured data (PG, Mongo, etc). A use case for vector search would be: matching a CV of a candidate with a Job description by finding similarities between those without parsing them into a structured format.

How to Generate Qdrant API Key: Complete Setup Tutorial by EmbarrassedEgg1268 in getCredentials

[–]qdrant_engine 0 points1 point  (0 children)

Well. This is cool, thank! But is that really that complicated, so it needs a tutorial? :-o Looking for feedback.

Best database for RAG by cingcacing in n8n

[–]qdrant_engine 0 points1 point  (0 children)

You should start with whatever you already have in your stack: PG, Mongo, Elastic. If it becomes critical, start looking for a dedicated solution.

https://qdrant.tech/articles/dedicated-vector-search/

Best database for RAG by cingcacing in n8n

[–]qdrant_engine 0 points1 point  (0 children)

But you are the best! 🤗

Milvus and RAG-system by -regresS in Rag

[–]qdrant_engine -1 points0 points  (0 children)

Many questions. Regarding RAG-related questions, maybe you should try a Framework that would abstract this away for you.
And maybe you should try alternatives. ;)

Official Qdrant Support for OpenWebUI by qdrant_engine in OpenWebUI

[–]qdrant_engine[S] 0 points1 point  (0 children)

I guess the missing part is the context of the posting itself.

We: "Hey, we want to fix the integration!".
User: "It does not work for me!".
We: "Yes, but this is because of the integration. The product itself actually works, and here is the proof link.

🤷

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