Qdrant
Open Source
High-performance vector database
Open-source core
Enterprise-ready deployments
Advanced search capabilities
Rust-powered efficiency
High-performance vector search engine for production-grade AI applications at any scale.
Last updated: Apr 15, 2026
FREEMIUM
qdrant.tech
Quick Answer
Qdrant is an open-source, high-performance vector database for AI retrieval and search. It offers advanced features like hybrid search, metadata filtering, and multivector support, built in Rust for speed and scalability. Best for developers and enterprises building production-grade AI applications, RAG systems, and AI agents. Available as open-source, free cloud tier, and paid managed cloud options.
About Qdrant
Qdrant is an open-source vector database designed for high-performance, full-feature vector search. It enables real-time retrieval for AI applications, supporting various deployment models including cloud, hybrid, and on-premise. Qdrant offers advanced metadata filtering, native hybrid search, and multivector capabilities for enhanced relevance.
What Makes It Unique
Qdrant is built entirely in Rust with SIMD and a custom storage engine (Gridstore) for highest performance and memory efficiency, offering real-time indexing and advanced quantization techniques for vector search.
Use Cases & Target Users
Use Cases
Best For
Building production-grade AI search applications
Implementing Retrieval Augmented Generation (RAG)
Developing intelligent AI agents with persistent memory
Powering personalized recommendation systems
Detecting anomalies and outliers in high-dimensional data
Company Size
SMALL
MEDIUM
ENTERPRISE
Fit Score
Complexity
ADVANCED
Target Team Size
SMALL_TEAM
LARGE_TEAM
Target Skill Level
INTERMEDIATE
EXPERT
Key Features
Expansive metadata filters (JSON, nested, text, geo)
Native hybrid search (dense + sparse) with BM25, SPLADE++, miniCOIL
Built-in multivector support for multimodal retrieval
Efficient one-stage filtering during HNSW traversal
Full-spectrum reranking with score boosting and MMR
Real-time indexing without rebuilding the entire index
Technical Specifications
API Available
SDK Available
MCP Compatible
Open Source
Apache-2.0
Team Features
SSO/Enterprise
Webhook Support
Has Demo
Deployment:
HYBRID
Compliance & Security
GDPR Compliant
SOC 2 Certified
Pros
- +Exceptional performance and scalability due to Rust-based architecture
- +Flexible deployment options: Managed Cloud, Hybrid Cloud, Private Cloud, Edge
- +Comprehensive features for advanced AI search, including hybrid search and reranking
- +Strong enterprise-grade security and compliance (SOC2, GDPR, HIPAA)
- +Developer-friendly with intuitive APIs and a built-in Web UI
- +Active open-source community and extensive documentation
Limitations
- -Free tier has limited resources (0.5 vCPU, 1GB RAM, 4GB Disk)
- -Advanced enterprise features like SSO and private VPC links are only available in Premium/Enterprise tiers
- -Cloud Inference with paid models requires tokens or specific tiers
- -Disk encryption with custom keys is currently AWS only
Uses Models
ColbertBM25SPLADE++
Decision Intelligence
Best For
Building production-grade AI search applications
Implementing Retrieval Augmented Generation (RAG)
Developing intelligent AI agents with persistent memory
Powering personalized recommendation systems
Detecting anomalies and outliers in high-dimensional data
Not Ideal For
Users needing a simple keyword-only search solution without vector capabilities
Small projects that do not require high-performance or scalable vector search
Non-technical users who prefer no-code solutions for data management
Applications that require offline-only vector search without Edge deployment
Frequently Asked Questions
Your Actions
Dimension Scores
Ease of Use8/10
Output Quality9/10
Value for Money8/10
Customization9/10
Support9/10
Integration8/10
Task Scores
Search Accuracy
10
Real Time Indexing
10
Multi Modal Search
10
Filter Refinement
10
Semantic Understanding
9
Personalization
9
Source Attribution
7
Answer Extraction
3
Trust Score
100/100
Excellent
Based on 11 verified signals
Trust Signals
Verified CompanyQdrant Solutions GmbH
Notable CustomersCanva, Hubspot, Bosch +7
User Base10K-100K
Funding$87.8M
Team Size51-200
Uptime SLA99.9%
Status PageView
GDPR CompliantYes
SOC 2 CertifiedYes
HIPAA CompliantYes
Data ResidencyNorth America (N. Virginia, N. California, Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Tokyo, Singapore, Sydney, Mumbai), South America (São Paulo). Also supports on-premise, hybrid, and edge deployments.
Switching & Migration
Migration Difficulty
Moderate Effort
Data portable as:
API
Community, Standard (10x5), Premium (24x7)
Quick Stats
CategorySearch
PlatformsWEB, API, CLI
Integrations16+
Views1
LaunchedJan 2020
Setup Time5 min
AddedMar 2026
Company & Links