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Qdrant

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

Profile Name

Star Rating

9
3
0
0
0

Qdrant Reviews

Review Filters
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