Qdrant vector database template
The Qdrant template defines a container with a 5 GB persistent volume and API-key authentication. Provisioning is currently unavailable in the international sandbox.
Qdrant template details
The template keeps Qdrant’s port private and configures an API key. Resource use and query performance depend on workload and configuration.
Qdrant vector database
Qdrant is written in Rust and provides vector search features. Resource requirements and query performance depend on data, workload, and configuration.
Qdrant marketplace template
The template defines a Qdrant container with a 5 GB persistent volume and API-key authentication. Provisioning is currently unavailable in the international sandbox.
Vector similarity and filtering
Qdrant supports vector search methods and metadata filtering. Search behavior depends on vector configuration, distance metric, data, and query design.
Private network access and authentication
The template keeps the Qdrant port private and configures an API key. Access from other services depends on network configuration; provisioning is currently unavailable in the international sandbox.
Frequently asked questions about Qdrant
Answers to common questions about vector search, Qdrant configuration, and application integration:
Qdrant vector search: features and deployment considerations
Qdrant is an open-source vector database used for similarity search. The Deplomo template defines a container with a persistent volume and API-key authentication; provisioning is currently unavailable in the international sandbox. Resource requirements depend on vector dimensions, index settings, and workload.
How does Qdrant search vectors?
Qdrant indexes vectors and supports similarity search, including approximate nearest-neighbor methods such as HNSW. Results depend on embeddings, index settings, and query design.
For relational data alongside vectors, you could use a database such as Postgresql host . Open WebUI can also be configured to work with a vector database such as Qdrant for document-retrieval workflows. See the open webui template for a separate local-model interface; these services are not preconfigured to work together.
Qdrant template compared with self-managed vector databases
Running a vector database requires planning storage, memory, indexes, access controls, and backup procedures. Resource needs depend on vector dimensions and workload; test representative data before choosing a configuration.
The Deplomo marketplace template defines a Qdrant container, a 5 GB persistent volume, and API-key authentication. Provisioning is currently unavailable in the international sandbox; performance and reliability depend on the deployment and workload.
Qdrant deployment options
Compare database features, configuration, resource requirements, and operating needs.
| Feature | Qdrant marketplace template | Relational database with vector features | Manual setup on a VPS |
|---|---|---|---|
| Vector search and indexing | Qdrant supports vector indexes and similarity search; performance depends on data and configuration | Performance depends on database, indexes, data, and workload | Requires configuration and testing for the selected workload |
| Setup and deployment | Template defines a container and persistent storage; provisioning currently unavailable | Extension availability depends on database and version | Self-managed setup requires configuration for storage, networking, and access |
| Metadata filtering | Qdrant supports payload filters; behavior and performance depend on query and index configuration | Features depend on database and configuration | Memory requirements vary with index and workload |
| Package pricing and resource limits | Fixed monthly EUR package prices by zone, with hard limits | Provider prices and limits depend on the selected service | Resource availability and package terms vary by provider |
Choose a vector database based on your data, retrieval requirements, resource needs, and operating model. Test retrieval quality with your own embeddings.
Qdrant template requirements and integration
Review the Qdrant template and its API requirements before deployment. Provisioning is currently unavailable in the international sandbox.
- Marketplace template The Qdrant template is listed in the marketplace; service provisioning is currently unavailable in the international sandbox.
- Review resource and storage needs Resource and storage limits are determined by the selected monthly EUR zone package. Plan for vector dimensions, indexes, and expected workload.
- API access The template configures an API key, but provisioning is currently unavailable in the international sandbox. No service address or deployment time is promised.
- Connect with a client library When a Qdrant service is available, configure a compatible client with the service address and API key. Check the client documentation for collection and vector setup.
Qdrant marketplace template summary
The marketplace lists a Qdrant container with persistent storage and API-key authentication. Provisioning is currently unavailable in the international sandbox; retrieval quality, performance, and capacity depend on configuration and workload.
Review the Qdrant template and its resource limits.
Review the Qdrant marketplace template
The template defines persistent storage and API-key authentication. Deplomo packages have fixed monthly EUR prices by zone and hard resource limits.