Qdrant

Open-source vector database for high-performance similarity search in AI applications — handles billions of vectors with ease.

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qdrant.tech
Verified API available Works with Make · n8n · Workato Free tier ~2.5k monthly visits
Quick facts
What is it Open-source vector database for high-performance similarity search in AI applications — handles billions of vectors with ease.
Pricing Freemium
Free tier Yes
Platform API
API Yes
Works with Make, n8n, Workato
Best for building recommendation systems, creating semantic search applications
Domain registered 2020

Data updated Aug. 1, 2026

What does Qdrant do?

Qdrant is an open-source vector database and similarity search engine specifically designed to handle high-dimensional vectors for AI applications. It serves as the backbone for neural network-based search, recommendation systems, and other AI-powered solutions that require efficient storage and retrieval of vector embeddings. The database excels at finding similar items in massive datasets by comparing their vector representations, making it essential for semantic search, image matching, and other similarity-based operations.

Built in Rust for maximum performance and reliability, Qdrant offers cloud-native scalability with both vertical and horizontal scaling options. It includes built-in compression techniques that dramatically reduce memory usage while maintaining search accuracy. The platform provides a lean, straightforward API that integrates easily with popular AI frameworks and embedding models, and can be deployed locally using Docker for testing or in production environments at enterprise scale.

Qdrant benefits developers building AI applications that require sophisticated search capabilities, such as e-commerce recommendation engines, content discovery platforms, and retrieval-augmented generation systems. Enterprise teams at companies like HubSpot, Bayer, and Bosch use it to power demanding AI applications that process billions of vectors while maintaining high performance and availability. It's particularly valuable for applications where response time and accuracy in similarity matching are critical to user experience.

#ai infrastructure#embedding-storage#high performance#neural search#open source#similarity search#vector database

Key features

What makes it stand out
01
Cloud-native scalability with vertical and horizontal scaling capabilities
02
Rust-powered performance for unmatched speed and reliability
03
Built-in compression options for dramatic memory usage reduction
04
Simple deployment with Docker and lean API for easy integration
05
Advanced search algorithms for multimodal data processing

Who is Qdrant for?

Who benefits most from this tool
building recommendation systems
creating semantic search applications
developing RAG (Retrieval-Augmented Generation) solutions

Pricing

Free tier available — start without a credit card

Managed Cloud

Free
  • 1GB free forever cluster
  • 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

Custom

Everything in Managed Cloud, plus:

  • All the benefits of Qdrant Cloud
  • Security, data isolation, optimal latency
  • Use the Managed Cloud Central Cluster Management
  • Standard support and uptime SLAs

Private Cloud

Custom

Everything in Hybrid Cloud, plus:

  • All the benefits of Hybrid Cloud
  • Security, data isolation, optimal latency
  • Manage Qdrant database clusters on your infrastructure
  • Premium Support Plan

Trust & presence

Domain Domain registered 2020

Gallery

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