Sold by: cloudimg
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This product has charges associated with it for seller support. Qdrant, the open source vector database for AI and similarity search, preinstalled and ready to use over a RESTful HTTP API. A per instance API key is generated on first boot. Backed by 24/7 cloudimg support.
Overview
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Listing collections over the REST API
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Inserting a vector with payload
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Nearest neighbour vector search
This is a repackaged open source software product wherein additional charges apply for cloudimg support services.
Overview Qdrant is an open source vector similarity search engine and vector database, written in Rust, that stores high dimensional vectors with rich payloads and serves them through a fast HTTP and gRPC API. It is widely used as the storage tier for retrieval augmented generation, semantic search, recommendation systems and any workload that needs to find the nearest neighbours of an embedding. This image delivers Qdrant fully installed and configured, so a complete vector database is running within minutes of launch.
Database Stack Qdrant running as a systemd service in single node mode. The Rust based engine carries no separate runtime dependency (no JVM, no Python, no Erlang), and the .deb installs the qdrant binary directly. The REST API is fronted on port 80 by an nginx reverse proxy with an api-key header guard, and the native Qdrant ports remain available for direct clients.
Secure First Boot On the first boot of your instance a one shot service generates a fresh Qdrant API key, unique to that instance, writes it into the Qdrant environment file, restarts Qdrant so the new key is applied, and stores the plain text value in a root only file. No shared or default credentials ship in the image, and every request to the database without the api-key header is rejected.
Ready To Use The Qdrant service, configuration, data directory and API key are all prepared. Send a request to the instance address with your api-key header to start creating collections, upserting vectors and running nearest neighbour searches. Collection segments are kept on a dedicated, independently resizable data disk.
cloudimg Support 24/7 technical support by email and chat. Help with Qdrant deployment, upgrades, collection design, indexing parameters and performance tuning.
Use Cases Vector storage for retrieval augmented generation pipelines. Semantic search across documents, products and media. Recommendation systems and personalisation. Anomaly detection on embeddings. Multimodal search combining text, image and audio vectors.
All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.
Highlights
- Qdrant vector database preinstalled and ready, with the RESTful HTTP API fronted on port 80 by nginx with an api-key header guard and no manual setup required
- Hardened first boot generates a fresh Qdrant API key for every instance and stores it in a file only the root user can read, so the database is never left open without authentication
- 24/7 technical support from cloudimg, with expert assistance for vector database deployment, collection design, indexing and performance tuning
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
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Try this product free for 7 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
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Dimension | Description | Cost/hour |
|---|---|---|
m5.large Recommended | m5.large | $0.08 |
t2.micro | t2.micro instance type | $0.04 |
t3.micro | t3.micro instance type | $0.04 |
c6id.12xlarge | c6id.12xlarge instance type | $0.24 |
g6.24xlarge | g6.24xlarge instance type | $0.24 |
m6in.12xlarge | m6in.12xlarge instance type | $0.24 |
g6f.large | g6f.large instance type | $0.08 |
c7a.xlarge | c7a.xlarge instance type | $0.12 |
g5.12xlarge | g5.12xlarge instance type | $0.24 |
t2.nano | t2.nano instance type | $0.00 |
Vendor refund policy
Refunds available on request.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Initial release of Qdrant 1 vector database.
Additional details
Usage instructions
Connect via SSH on port 22 as the default login user for your operating system variant (the user guide lists it per variant). Qdrant serves the REST API on port 6333 directly and on port 80 via nginx; the gRPC API is bound to localhost only by default for security. Every request must include an 'api-key' header. Retrieve the generated key with: sudo cat /root/qdrant-credentials.txt. Probe the database with: curl -H "api-key: <key>" http://<instance-public-ip>/collections. Restrict ports 80 and 6333 to trusted networks. The user guide covers creating collections, upserting vectors, running searches and accessing gRPC over an SSH tunnel.
Resources
Vendor resources
Support
Vendor support
cloudimg provides 24/7 technical support for this product by email and live chat. Our engineers help with deployment, configuration, updates, performance tuning and troubleshooting; critical issues receive a one hour average response. Contact support@cloudimg.co.uk .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Qdrant is an open-source and fully managed high-performance Vector Database. The vector search engine provides a production-ready service with a convenient API to store, search, and manage vector embeddings.
Qdrant is an open-source and fully managed high-performance Vector Database. The vector search engine provides a production-ready service with a convenient API to store, search, and manage vector embeddings.
This product has charges associated with it for seller support. Qdrant is an open source, high performance vector database and similarity search engine designed for AI, machine learning, and semantic search applications.
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