What it does
Core capabilities at a glance
- Rust-based high-performance vector engine
- Rich payload filtering and indexing
- Scalar, product, and binary quantization
- Multi-tenancy with isolated collections
- Distributed deployment with replication
- REST and gRPC APIs with client SDKs
Deep dive
The full breakdown - performance, comparisons, and setup
Qdrant
Qdrant is the vector database you choose when you care about search quality and filtering performance. Written in Rust, it delivers consistent low-latency vector search with payload filtering that most other vector databases can't match.
What it is
Qdrant is a vector similarity search engine that stores vectors alongside payload data (metadata) and allows filtering on that metadata before or during the search. It's designed for production RAG applications where you need to search across millions of vectors with complex business logic filters.
Performance you'll see
| Hardware | Vectors | Latency (p99) | Recall |
|---|---|---|---|
| Single server (64GB RAM) | 10M vectors at 768d | under 50ms | 0.99 |
| Single server (128GB RAM) | 50M vectors at 768d | under 100ms | 0.98 |
| 3-node cluster | 500M vectors at 768d | under 200ms | 0.98 |
How it stacks up
| Qdrant | Chroma | Milvus | Weaviate | |
|---|---|---|---|---|
| Written in | Rust | Python | Go/C++ | Go |
| Filtering | Best | Good | Great | Great |
| Quantization | Yes (scalar, product, binary) | No | Yes | Yes |
| Distributed | Yes | No | Best | Yes |
| Ease of setup | Medium | Easy | Hard | Medium |
| Best for | Production RAG | Prototyping | Billion-scale | All-in-one |
Get started
docker run -d -p 6333:6333 qdrant/qdrantWhen to use something else
From the community
What users are saying
“Many: https://testimonial.to/qdrant/all https://techcrunch.com/2024/01/23/qdrant-open-source-vector-...”
“Qdrant is the vectordb that ChatGPT and Grok use (e.g. when you add docs to a custom GPT or tweets in Grok) https://twitter.com/simonw/status/1722011967886688696”
“We are for a few projects. We've been using them for over a year and have been impressed. We have 10s millions of items in there with lots of daily inserts/deletions etc. There's been a couple of gotchas but generally it is quite predictable and scalable.”
Frequently asked
Quick answers to common questions
What is Qdrant?
Qdrant is a vector-db tool for local AI workloads. High-performance vector search engine written in Rust with rich filtering and full payload support.
Is Qdrant free and open source?
Yes, Qdrant has 35,130 GitHub stars and is licensed under Apache-2.0. You can self-host it for free on docker, linux, macos, windows.
What platforms does Qdrant support?
Qdrant runs on docker, linux, macos, windows.
What hardware do I need for Qdrant?
The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. Qdrant has 35,130 GitHub stars and an active community.
Does Qdrant support GPU acceleration?
Qdrant supports GPU acceleration via CUDA, Metal, or Vulkan depending on your platform. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.
What are the best alternatives to Qdrant?
Popular alternatives include other vector-db tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.
How much does Qdrant cost?
Qdrant is freemium. Check the official website for current pricing.
Pairs well with
Complementary tools, models, and hardware