Base
Hardened build
minimal ports, security patches applied at build time
Qdrant
Azure
Databases
2 variations
A high performance open source vector similarity search engine and database, with a built in dashboard.
Variations
Choose the operating system, cloud and version you need. Every variation is the same hardened Qdrant image, built and supported by cloudimg.
| Product | Cloud | Operating system | Version | |
|---|---|---|---|---|
| Qdrant 1.16 on Ubuntu 22.04 | Azure | Ubuntu 22.04 | 1.16 | View · Guide |
| Qdrant on Ubuntu 24.04 | Azure | Ubuntu 24.04 | Standard | View · Guide |
Overview
Qdrant is a high performance open source vector similarity search engine and vector database, written in Rust for speed and reliability under heavy load. It stores points made of a vector and a JSON payload, indexes them with HNSW, and answers nearest neighbour, filtered and hybrid search queries in milliseconds through a clean REST and gRPC API, with official client libraries for Python, JavaScript, Rust, Go and more.
It suits any team building semantic search, recommendations, retrieval augmented generation or anomaly detection that wants a fast vector database they run and own inside their own cloud account rather than a hosted service.
Why the cloudimg image
The cloudimg image installs Qdrant from the official release behind an nginx reverse proxy that binds the engine to loopback and terminates TLS, so the REST and gRPC API and the built in dashboard are reachable securely within minutes. Security is enforced from the first request: a unique API key is generated on each virtual machine's first boot and written to a root only file, and the service is configured to refuse to start without one, so there is no open unauthenticated API and no shared credential in the image. Vector data lives on a dedicated data disk. The paired deployment guide covers reading your key, creating a collection, upserting vectors, running your first search and enabling a real TLS certificate, and every deployment carries 24/7 support.
Common uses
- Semantic search and retrieval augmented generation over your own embeddings
- Recommendations, similarity matching and anomaly detection at scale
- A self hosted vector database you run inside your own cloud account
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