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Qdrant

Qdrant is a vector similarity search engine that provides a production-ready service with a convenient API to store, search, and manage points (i.e. vectors) with an additional payload. You can think of the payloads as additional pieces of information that can help you hone in on your search and also receive useful information that you can give to your users.

1 APIs 16 Features
AIArtificial IntelligenceVector Databases

APIs

Qdrant API

Qdrant (read: quadrant) is a vector similarity search engine. Use our documentation to develop a production-ready service with a convenient API to store, search, and manage vect...

Features

Free Tier: single-node 0.5 vCPU / 1 GB RAM / 4 GB disk
Standard: usage-based dedicated resources, 99.5% SLA
Premium: SSO, private VPC, 99.9% SLA
Hybrid Cloud: runs on your infra, managed via Qdrant Cloud
Private Cloud: dedicated isolated deployment
REST and gRPC APIs
Throughput scales with cluster resources
Batch upsert up to 10,000 points/request
Sparse vectors and hybrid search
Quantization (scalar, binary, product)
Snapshot backup / restore
Multi-tenancy via collections + payload filtering
Distributed deployment with sharding
Web UI for collection management
Cloud Inference for embeddings (selected models free)
Open-source self-hosted alternative

Resources

👥
GitHubOrganization
GitHubOrganization
🔗
LinkedIn
LinkedIn
🚀
GettingStarted
GettingStarted
🔗
Documentation
Documentation
🎓
Tutorials
Tutorials
💰
Pricing
Pricing
📰
Blog
Blog
🔗
Website
Website
🔗
LLMsTxt
LLMsTxt

Sources

Raw ↑
aid: qdrant
name: Qdrant
description: >-
  Qdrant is a vector similarity search engine that provides a production-ready service with a convenient API to store,
  search, and manage points (i.e. vectors) with an additional payload. You can think of the payloads as additional
  pieces of information that can help you hone in on your search and also receive useful information that you can give
  to your users.
type: Index
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
tags:
  - AI
  - Artificial Intelligence
  - Vector Databases
url: https://raw.githubusercontent.com/api-evangelist/qdrant/refs/heads/main/apis.yml
created: '2024-06-18'
modified: '2026-05-19'
specificationVersion: '0.19'
apis:
  - aid: qdrant:qdrant-api
    name: Qdrant API
    tags:
      - AI
      - Artificial Intelligence
      - Vector Databases
    humanURL: https://qdrant.tech/documentation/
    properties:
      - url: https://qdrant.tech/documentation/
        type: Documentation
      - url: openapi/qdrant-openapi-original.json
        type: OpenAPI
    description: >-
      Qdrant (read: quadrant) is a vector similarity search engine. Use our documentation to develop a production-ready
      service with a convenient API to store, search, and manage vectors with an additional payload. Qdrant's expanding
      features allow for all sorts of neural network or semantic-based matching, faceted search, and other applications.
common:
  - type: GitHubOrganization
    url: https://github.com/qdrant
  - type: LinkedIn
    url: https://www.linkedin.com/company/qdrant
  - url: https://qdrant.tech/documentation/quick-start/
    type: GettingStarted
  - url: https://qdrant.tech/documentation/concepts/
    type: Documentation
  - url: https://qdrant.tech/documentation/tutorials/
    type: Tutorials
  - url: https://qdrant.tech/pricing/
    type: Pricing
  - url: https://qdrant.tech/blog/
    type: Blog
  - url: https://qdrant.tech
    type: Website
  - type: Features
    data:
      - 'Free Tier: single-node 0.5 vCPU / 1 GB RAM / 4 GB disk'
      - 'Standard: usage-based dedicated resources, 99.5% SLA'
      - 'Premium: SSO, private VPC, 99.9% SLA'
      - 'Hybrid Cloud: runs on your infra, managed via Qdrant Cloud'
      - 'Private Cloud: dedicated isolated deployment'
      - REST and gRPC APIs
      - Throughput scales with cluster resources
      - Batch upsert up to 10,000 points/request
      - Sparse vectors and hybrid search
      - Quantization (scalar, binary, product)
      - Snapshot backup / restore
      - Multi-tenancy via collections + payload filtering
      - Distributed deployment with sharding
      - Web UI for collection management
      - Cloud Inference for embeddings (selected models free)
      - Open-source self-hosted alternative
    sources:
      - https://qdrant.tech/pricing/
    updated: '2026-05-04'
  - type: Integrations
    url: https://qdrant.tech/partners/
  - type: LLMsTxt
    url: https://qdrant.tech/llms.txt
integrations:
  - name: logo
  - name: Partners logos
  - name: AWS marketplace
  - name: Google Cloud marketplace
  - name: Microsoft Azure
  - name: Tara Walker Avatar
  - name: Cohere
  - name: Gemini
  - name: OpenAI
  - name: Aleph Alpha
  - name: Jina
  - name: AWS
  - name: 1M-Open-AI-Embeddings
  - name: LangChain
  - name: LlamaIndex
  - name: Airbyte
  - name: Unstructured
  - name: DocArray
  - name: AutoGen
  - name: Traversaal.ai
  - name: Domino
  - name: Revelry
  - name: Softlandia
  - name: Qdrant
  - name: SOC2
  - name: heyData GDPR
  - name: GDPR
  - name: HIPAA
maintainers:
  - FN: Kin Lane
    email: kin@apievangelist.com