Qdrant
Open-source vector database for semantic search and AI applications
What it does well
- Exceptional query performance with sub-millisecond latencies at scale
- Rich filtering and hybrid search combining vectors with metadata/text search
- Flexible deployment: self-hosted, cloud, or fully managed options
- Strong production features including clustering, replication, and high availability
Where it falls short
- Smaller ecosystem and community compared to established vector databases
- Managed cloud pricing can be costly for very large-scale deployments
- Steeper learning curve for teams new to vector database concepts and operations
Core Features
| Vector Search Engine | Yes |
| Similarity Search | Yes |
| Filtering & Metadata | Yes |
| REST API | Yes |
| gRPC API | Yes |
| HNSW Algorithm | Yes |
| Distributed Search | Yes |
| Multi-vector Support | Yes |
| Payload Indexing | Yes |
| Cloud Deployment | Yes |
| Self-Hosted Option | Yes |
Security
| Role-Based Access Control | Yes |
| TLS Encryption | Yes |
Open Source
Free
- Self-hosted vector database
- Full API access
- Community support
- Unlimited collections
- Semantic search capabilities
Qdrant Cloud Starter
$25/mo
$250/yr billed annually
- Managed cloud hosting
- 1GB storage
- API access
- Email support
- Automated backups
- High availability
Qdrant Cloud Professional
$149/mo
$1490/yr billed annually
- Everything in Starter
- 50GB storage
- Priority support
- Advanced monitoring
- Custom VPC options
- SLA guarantee
Qdrant Cloud Enterprise
Custom
- Everything in Professional
- Unlimited storage
- 24/7 dedicated support
- Custom deployment options
- Advanced security features
- Custom SLA
Comparisons with Qdrant
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