Qdrant Reviews

My primary use cases for Qdrant are legal and educational.

The most valuable feature I have found in Qdrant is the sample code. I think they have good examples that make it developer-friendly.

Using Qdrant's hybrid search capability has improved my search results. The ability of Qdrant to handle high-dimensional vectors for my AI projects is pretty fast, and I think it's the best we have used so far. That's why we continue using it and did not check other options anymore.

The configuration of Qdrant is okay. For a developer, it was easy to set the product up and to use it.

I should check if real-time data updates in Qdrant have helped improve my models, as I don't even know they have that feature.

A lot of our work is agentic right now, and we have also segmented the content to be logical, so there's not a lot of vector search anymore. I haven't really thought of any additional features that would make Qdrant closer to a perfect score.

I have been using Qdrant for two years.

I would rate Qdrant's technical support as community-driven. There's community support since we're not paying anything, and it's more the community support for it. It's open source, so we house it on our server.

I think they provide enough information on the internet, and I am satisfied with it. They explain it well.

I switched from Faiss because it's open source and there's not a lot of support. We were worried that moving forward, maybe no one will maintain it, so it's just good for experimenting.

The configuration of Qdrant is okay. For a developer, it was easy to set the product up and to use it.

Using Qdrant is free. We house it and have a VM where we just installed it on the VM.

Before finally choosing Qdrant, I did evaluate other options, but that was a long time ago, and I don't know what the state of vector databases is now.

Currently, we are using a vector database called Qdrant, but most of our tasks are agentic, and we don't have it anymore. I can answer a few questions about Qdrant.

I have used Qdrant's hybrid search capability. The use of multiple query languages has impacted my data query processes mostly as Q&A.

We use the Ragas metrics to evaluate Qdrant's performance in indexing and retrieving vectors. All the metrics I consider in Ragas are useful.

In my company, we have around eight or nine people using Qdrant. I think Qdrant is popular enough in my region, but they can probably promote it more.

I rate this review a 9 out of 10.