Qdrant
An open-source vector database designed for high-performance similarity search and storage of embeddings.
Configuration
services:
qdrant:
image: "qdrant/qdrant:latest"
environment:
- SERVICE_FQDN_QDRANT_6333
- QDRANT__SERVICE__API_KEY=${QDRANT_API_KEY}
expose:
- "6333"
volumes:
- "qdrant_data:/qdrant/storage"
healthcheck:
test:
- CMD-SHELL
- bash -c ':> /dev/tcp/127.0.0.1/6333' || exit 1
interval: 5s
timeout: 5s
retries: 3
volumes:
qdrant_data: {}[variables]
main_domain = "${domain}"
[config]
mounts = []
[[config.domains]]
serviceName = "qdrant"
port = 6333
host = "${main_domain}"
[config.env]
QDRANT_API_KEY = "${password:32}"Base64
To import this template in Dokploy: create a Compose service → Advanced → Base64 import and paste the content below:
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Tags
vector-db, database, search
Version: latest