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Qdrant

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12 reviews
  • 2 profiles
  • 3 categories
Average star rating
4.5
Serving customers since
2021

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Star Rating

9
3
0
0
0

Qdrant Reviews

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Profile Name
Star Rating
9
3
0
0
0
Rishi K.
RK
Rishi K.
05/29/2025
Validated Reviewer
Review source: G2 invite
Incentivized Review

scalability & availability

fully manage in all resource ,available on AWS , Google and azure plaform help with vector search technolgy
KJ
Kawalpreet J.
12/12/2024
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

A quick and easy to setup vector database for RAG needs

In our organization, we developed an RAG application and needed a way to store embeddings. I looked after many open-source tools like Pinecone and Superduperdb. Qdrant worked the best. The setup on our server was super easy, and their documentation is very elaborate. I also think the embedding search is more accurate than the other platforms I piloted with. We are still currently using Qdrant for our RAG application and are happy with it.
AM
Aarav M.
11/28/2024
Validated Reviewer
Verified Current User
Review source: Organic

Self-hosted Qdrant Vector DB

Self-hosting Qdrant on a host is really simple and does not takes a lot of time to setup or troubleshoot issues. The documentation is also up to date. I prefer to install it using Docker to avoid installing dependencies.

About

Contact

HQ Location:
Berlin, Berlin

Social

@qdrant_engine

What is Qdrant?

Qdrant is the leading, high-performance, scalable, open-source vector database and search engine, essential for building the next generation of AI/ML applications. Qdrant is able to handle billions of vectors, supports the matching of semantically complex objects, and is implemented in Rust for performance, memory safety, and scale.

Details

Year Founded
2021
Website
qdrant.tech