Qdrant
High-performance open-source vector database and similarity search engine designed for AI applications at massive scale.
At a Glance
About Qdrant
Qdrant is a leading open-source vector database and similarity search engine designed to handle high-dimensional vectors for performance and massive-scale AI applications. Built in Rust for unmatched speed and reliability, it powers advanced search, recommendation systems, retrieval-augmented generation (RAG), data analysis, anomaly detection, and AI agents. Qdrant offers flexible deployment options including managed cloud, hybrid cloud, and private cloud solutions.
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High-Performance Vector Search - Purpose-built in Rust to process billions of vectors with exceptional speed and reliability, delivering enterprise-grade performance for demanding AI workloads.
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Cloud-Native Scalability - Enterprise-grade managed cloud with vertical and horizontal scaling, zero-downtime upgrades, and high availability across AWS, Google Cloud, and Azure.
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Flexible Deployment Options - Choose from fully managed cloud, hybrid cloud (bring your own Kubernetes clusters), or private cloud for maximum control and data sovereignty.
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Cost Efficiency with Quantization - Dramatically reduce memory usage with built-in compression options and offload data to disk for optimized resource utilization.
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Advanced Filtering & Payload Support - Combine vector similarity search with payload filtering for nuanced queries and multimodal data handling.
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Easy Integration - Integrates with all leading embeddings and frameworks, with SDKs for Python, JavaScript, Rust, Go, and more.
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Enterprise Security - SOC2 Type 2 certified with RBAC, SSO, granular API keys, and GDPR compliance support for regulated environments.
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Monitoring & Observability - Built-in support for Prometheus/OpenMetrics, Datadog, Grafana, and other third-party monitoring integrations.
To get started, deploy Qdrant locally with Docker using docker pull qdrant/qdrant and docker run -p 6333:6333 qdrant/qdrant, or sign up for Qdrant Cloud with a free 1GB cluster. The comprehensive documentation and quick start guide help developers build production-ready vector search applications for matching, searching, and recommending.
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Pricing
Free Tier
1GB free forever cluster, no credit card required
- 1GB free cluster
- Fully managed
- Multiple cloud providers (AWS, GCP, Azure)
- Central monitoring
- Unlimited users
Managed Cloud
Scale your production solutions without deployment and upkeep
- Fully managed with central cluster management
- Multiple cloud providers and regions (AWS, GCP, Azure)
- Horizontal & vertical scaling
- Central monitoring, log management and alerting
- High availability, auto-healing
- Backup & disaster recovery
- Zero-downtime upgrades
- Unlimited users
- Standard support and uptime SLAs
Hybrid Cloud
Bring your own cluster from any cloud provider, on-premise infrastructure, or edge locations
- All the benefits of Qdrant Cloud
- Security, data isolation, optimal latency
- Use the Managed Cloud Central Cluster Management
- Standard support and uptime SLAs, can be upgraded to Premium
Private Cloud
Deploy Qdrant fully on premise for maximum control and data sovereignty
- All the benefits of Hybrid Cloud
- Security, data isolation, optimal latency
- Manage Qdrant database clusters on your infrastructure
- On-premise, at the edge, even fully air-gapped
- Premium Support Plan
Capabilities
Key Features
- High-dimensional vector similarity search
- Cloud-native scalability with horizontal and vertical scaling
- Built-in quantization for memory optimization
- Payload filtering and metadata support
- Multimodal data handling
- Zero-downtime upgrades
- High availability and auto-healing
- Backup and disaster recovery
- Role-based access control (RBAC)
- Single sign-on (SSO)
- Prometheus/OpenMetrics monitoring
- Datadog and Grafana integration
- REST and gRPC APIs
- Docker deployment
- Terraform support
- Multiple distance metrics
- Recommendation API
- Hybrid cloud deployment
- Private cloud deployment
- SOC2 Type 2 certification