Qdrant

Qdrant is an Open-Source Vector Search Engine that provides fast and scalable vector similarity search. It helps build high-performance AI retrieval systems at any scale and deployment model.

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At a glance

Pricing

Freemium · Enterprise · Usage-based · Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Qdrant?

Qdrant is an open-source vector search engine written in Rust, designed for high-performance and scalable vector similarity search. It enables developers to build advanced AI retrieval systems, supporting expansive metadata filters, native hybrid search (dense + sparse), and built-in multivector capabilities. Qdrant offers efficient, one-stage filtering and full-spectrum reranking to enhance relevance. It can be deployed anywhere, including Qdrant Cloud, Hybrid Cloud, Private Cloud, and Edge (Beta), with enterprise-ready tooling like SOC 2 compliance, Prometheus/Grafana integration, and SSO. Its architecture is optimized for AI, featuring real-time indexing, memory-efficient storage, and advanced quantization techniques, making it suitable for production-grade AI search applications.

Best used for

Ideal for data scientists and AI engineers who need to build high-performance AI retrieval systems, implement advanced RAG applications, and power intelligent AI agents. Especially valuable for those requiring scalable vector search with robust filtering and deployment flexibility across cloud, hybrid, or edge environments.

Common actions

build AI retrieval

perform vector search

manage vector data

scale AI applications

implement RAG

startup tools

Capabilities

Key features

Vector similarity search
Expansive metadata filters
Native hybrid search
Built-in multivector support
Real-time indexing
Memory-efficient storage
Advanced quantization techniques

Target Audience

data scientistdeveloperAI engineer

Integrations

prometheusgrafanadatadog

Pricing & Plans

Freemium · Enterprise · Usage-based · Open Source

Paid

FAQs

What is the difference between Qdrant Cloud, Hybrid Cloud, and Private Cloud?

Qdrant Cloud is fully managed by Qdrant. Hybrid Cloud allows you to use your own infrastructure with Qdrant's management plane. Private Cloud offers dedicated, isolated deployments for strict security or air-gapped setups, providing maximum control and custom SLAs.

What are the limits of the Qdrant Free Tier?

The Free Tier is designed for testing and prototypes, offering a single-node cluster with 0.5 vCPU, 1GB RAM, and 4GB Disk. It also includes free cloud inference with selected models. If your data grows beyond these limits, you can easily upgrade to a Standard Tier.

Does Qdrant support hybrid search and multivector capabilities?

Yes, Qdrant natively supports hybrid search, blending keyword and vector search in one query using dense or sparse vectors, including BM25, SPLADE++, and miniCOIL. It also features built-in multivector support, allowing multiple vectors per object for enhanced relevance.

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Subcategories trending in AI Agents & Automation

Chatbots & Conversational AI General-Purpose Agents Workflow Agents Personal Assistants RAG & Document AI Voice Agents

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Coding & Development › Database & SQL Coding & Development › Open Source & Models Data & Analytics › Predictive Analytics

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