"Efficient, scalable vector search engine for high-performance AI, ML, and semantic search applications"
Typical plan: $10 / month
- 1 reviews
- 5.0
- Monthly users
- 178K
- Pricing
- $0 – $25 / month
- Platform
- Web App · API
Overview
Qdrant is an advanced, high-performance vector database and search engine optimized for similarity search on large-scale, high-dimensional datasets. It features fast and efficient indexing (including HNSW), payload-based filtering, advanced compression techniques, distributed cloud-native architecture, multitenancy, easy-to-use APIs, enterprise-grade secu...
Efficient, scalable vector search engine for high-performance AI, ML, and semantic search applications
Tool Details
Pricing opens by default; expand other sections for key facts, compliance, specs, and provider info. The main column keeps the quick summary.
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Key Features
Developer-friendly API
RESTful API design follows industry standards for easy integration.
Client libraries available
Type-safe SDKs provide autocomplete and compile-time checks for faster development.
Open-source transparency
Open source means community feedback, transparent security, and rapid iteration.
Built for regulated teams
Qdrant aligns with common compliance frameworks so regulated industries can adopt AI safely. Qdrant may fit security-sen
Support & service excellence
Qdrant unifies tickets, context, and communication so agents resolve faster. Qdrant is relevant for support workflows wh
Expert Insight
Albert Schaper(Artificial Intelligence, AI Tools)
Albert Schaper endorses Qdrant for Search & Discovery applications. Albert Schaper's knowledge of artificial intelligence makes this assessment particularly valuable for software developers seeking Search & Discovery solutions.
Pricing & Plans
Pricing: $0 – $25 / month(Updated September 2025)
Free 1GB cloud forever tier. Managed Cloud hourly from $0.014/hr (~$10/month). Paid Community plan from $25/month. Enterprise/Private Cloud: contact for pricing.
Usage Model: API Calls, Storage — ensuring you only pay for what you actually use.
Qdrant offers free access to search & discovery tools, ideal for software developers getting started. The free tier includes essential features that enable basic workflows and learning. When you need more, paid plans unlock advanced functionality, increased limits, and priority support for software developers building serious search & discovery solutions.
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About Qdrant
“Efficient, scalable vector search engine for high-performance AI, ML, and semantic search applications”
Qdrant Snapshot
Key facts we track so you can judge fit before visiting the provider.
- Primary category
- Search & Discovery
- Best fit
- Software Developers, Scientists, Entrepreneurs +4 more
- Platforms
- Web App, API
- Pricing signal
- Freemium, Enterprise +1 more - $0-$25 / month
- Provider context
- Qdrant - DE
- Developer access
- API documentation, Python, Go
- Data handling
- Global hosting, Privacy policy linked
- Evidence signals
- 178K monthly visits, 5.0 rating from 1 reviews, 4 community favorites +1 more
Before you choose Qdrant
- Confirm Qdrant's current limits, renewal terms, and seat pricing on the official site.
- Review privacy, retention, and data-processing terms before using sensitive data.
- Test the integrations or API path against one real workflow before rollout.
- Make sure the supported platform matches where your team actually works.
Listing data is compiled from structured provider information, public signals, submissions, and periodic checks where available. Treat this page as a shortlist aid, then verify pricing, compliance, and product limits with the provider before making a business-critical decision.
How Qdrant Works
Understanding the core functionality and approach of Qdrant.
Custom pricing ensures Qdrant fits high-scale or regulated deployments. The vendor works with stakeholders to scope rollout, enablement, and ongoing support. Qdrant offers custom enterprise plans; sales will model pricing for your requirements.
Key Features
Explore what makes Qdrant stand out.
Developer-friendly API
RESTful API design follows industry standards for easy integration.
Client libraries available
Type-safe SDKs provide autocomplete and compile-time checks for faster development.
Open-source transparency
Open source means community feedback, transparent security, and rapid iteration.
Built for regulated teams
Qdrant aligns with common compliance frameworks so regulated industries can adopt AI safely. Qdrant may fit security-sensitive workflows if its logging, access control, and data handling meet your standards.
Support & service excellence
Qdrant unifies tickets, context, and communication so agents resolve faster. Qdrant is relevant for support workflows when it connects cleanly to tickets, knowledge bases, or customer context.
Use Cases
Discover how different audiences leverage Qdrant.
Enhance developer productivity
Engineering keeps ownership of customization while leveraging managed AI capabilities.
Product roadmap planning
Launch reviews and retrospectives stay organized in one place.
Secure deployments
Security teams monitor access, compliance, and audit trails inside Qdrant.
FAQ about Qdrant
What is Qdrant and what does it do?
How much does Qdrant cost?
Is Qdrant secure and compliant with data privacy regulations?
What platforms does Qdrant support?
How can I try Qdrant before purchasing?
What file formats does Qdrant support?
Who develops and maintains Qdrant?
How do I get access to Qdrant?
How is usage measured and billed in Qdrant?
What deployment options does Qdrant offer?
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Keep Qdrant's listing accurate
Providers can update product facts, pricing context, screenshots, and launch notes. Paid placements are labeled separately and do not replace editorial or data-quality review.
How to Evaluate Qdrant
Use this page to evaluate Qdrant alongside similar search & discovery tools in our alternatives overview. The goal is not to pick the most popular product; it is to find the tool that fits your actual workflow, risk level, and budget.
- Step 1Test Qdrant with one real workflow before moving important work into it.
- Step 2Model the full monthly cost at your expected usage, including seats, limits, and overages.
- Step 3Verify the integration path with your existing stack before you commit.
- Step 4Review privacy, retention, and compliance terms before using sensitive data.
For developer teams, inspect the Python SDK and Go support. Review the API documentation for auth, rate limits, errors, and export behavior. For broader context, browse more search & discovery tools for software developers, or compare this page against the category hub. New to AI tool evaluation? Start with AI Tool Navigator.
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