Qdrant
by Qdrant
At a glance
Vector search engine for semantic retrieval with payload filters and hybrid query support.
vector developer-tools
- Licence
- Not recorded
- Category
- Platforms & Infrastructure
- Business model
- Freemium
- Availability
- Not recorded
- Launched
- Not recorded
Overview
Typical uses include Semantic retrieval for RAG; Search over embedded application data. Documented capabilities: Dense, sparse and multivector retrieval; Payload filtering and hybrid queries; Self-hosted server and managed cloud deployment.
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Key features
- Dense, sparse and multivector retrieval
- Payload filtering and hybrid queries
- Self-hosted server and managed cloud deployment
Use cases
- Semantic retrieval for RAG
- Search over embedded application data
Pricing
Open-source Qdrant can be self-hosted. Cloud Free includes 1 GB RAM and 4 GB disk; Standard is resource-based for a dedicated cluster. Embedding-provider costs and larger-cluster charges are separate from the free database tier.
Record details
Provenance, dates and links are kept here so the main sections stay about the product itself.
Links, dates and provenance
- Record updated
- 2026-11-03
- Pricing
- qdrant.tech ↗
- Documentation
- qdrant.tech ↗
- Canonical URL
- https://globalaiproductindex.com/products/qdrant/
Selection profile
Every field says where its value comes from. "Unknown" means we have not confirmed it — it does not mean the product lacks the feature.
Selection profile11 fields6 unknown
- Tasks it fits
- Search
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - How you use it
- Self-run service
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - Runs on
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Where it runs
- Vendor cloud Self-hosted
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - Works offline
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Official service region
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Public API
- Yes
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - Licence
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Commercial use
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Interface languages
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Billing
- Open source Usage-based Free allowance: Limited Subscription required: No
Prices are the vendor’s advertised entry price and exclude taxes; always confirm on the vendor’s own page.
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Where each value comes from
- Tasks it fits
- Our inference
- How you use it
- Our inference
- Runs on
- Unknown
- Where it runs
- Our inference
- Works offline
- Unknown
- Official service region
- Unknown
- Public API
- Our inference
- Licence
- Unknown
- Commercial use
- Unknown
- Interface languages
- Unknown
Key facts and their evidence
Each fact lists the conditions it holds under, the page it was read from and the day it was checked.
-
Capability: Dense, sparse and multivector retrieval Verified 2026-11-03 qdrant.tech ↗
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Frequently asked questions
Where does Qdrant fit in a workflow?
Vector search engine for semantic retrieval with payload filters and hybrid query support. Dense, sparse and multivector retrieval.
What costs and limits should I compare before choosing Qdrant?
Open-source Qdrant can be self-hosted. Cloud Free includes 1 GB RAM and 4 GB disk; Standard is resource-based for a dedicated cluster. Embedding-provider costs and larger-cluster charges are separate from the free database tier.
Similar products
- Chroma — Retrieval infrastructure with an open-source database and serverless cloud search.
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- Milvus — Open-source vector database that scales from an embedded library to distributed retrieval clusters.
- turbopuffer — Object-storage-native search engine for vector and full-text retrieval with cached compute.
- Vespa — Search and ranking platform combining vector retrieval, lexical search and model-based relevance.
- Andi — Conversational AI search engine that answers questions and summarizes pages instead of showing ad-driven links.
All Qdrant alternatives → · All Platforms & Infrastructure products →
Sources
- Qdrant — official product ↗
- Qdrant — official documentation and terms ↗
- Qdrant — official documentation and terms ↗
This record was last reviewed on 2026-11-03.
Machine-readable record: /api/products/qdrant.json · Spot an error? Suggest a correction