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Fast, open-source vector search written in Rust
Overall score
88/100
Verdict
Excellent
Pricing
Free
Performance radar — Qdrant
Score breakdown
Developer UX
SDK quality, indexing API, and setup speed.
Source: RadarTrek research
Query Performance
ANN search speed and recall accuracy at scale.
Source: RadarTrek research
Scalability
Index size limits and horizontal scaling for billions of vectors.
Source: RadarTrek research
Price / Value
Cost per million vectors and free tier generosity.
Source: RadarTrek research
Hybrid Search
Combining vector similarity with keyword/metadata filtering.
Source: RadarTrek research
Ecosystem
LangChain/LlamaIndex integrations and framework support.
Source: RadarTrek research
Qdrant is an open-source vector database built in Rust for performance, with excellent filtering capabilities alongside vector search. Self-host for free or use Qdrant Cloud.
In our independent evaluation across 6 scored dimensions, Qdrant earns an overall score of 88/100 — a excellent result in the vector databases category. The platform is available including a permanently free tier, accessible to teams at any budget level. The score of 88 places it in the excellent tier of our vector databases rankings, where we assess tools on criteria that matter to builders: developer ux, query performance, scalability, and more.
Qdrant scores highest on Query Performance (92/100) and Developer UX (88/100), placing it among the stronger performers in those areas within the vector databases category. The dimensions with the most room for improvement are Ecosystem (82/100) and Hybrid Search (85/100) — teams who weight these criteria most heavily should compare Qdrant carefully against alternatives before committing. The free entry point makes it easy to validate Qdrant before committing to a paid plan — a practical advantage when evaluating a new tool category. Our recommendation: Qdrant is worth a serious evaluation for teams that prioritise query performance — use the radar chart and dimension breakdown on this page to see at a glance whether its profile matches your priorities.
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Yes — Qdrant is free to use with no trial period or credit card required. It offers a permanently free tier, though paid plans with higher limits or additional features are typically available. Check the official pricing page for current plan details.
Qdrant scores highest on Query Performance in our independent assessment — 92/100, placing it among the stronger performers in this dimension within the vector databases category. ANN search speed and recall accuracy at scale.. Teams who count query performance as a primary criterion should put Qdrant high on their evaluation list.
The lowest-scoring dimension for Qdrant in our testing is Ecosystem (82/100). This does not make it the wrong choice — if ecosystem is not a priority for your use case, the gap is irrelevant. But teams who weight ecosystem most heavily should compare Qdrant carefully against alternatives before committing, using the radar chart on this page to see the full profile at a glance.
Qdrant earns an overall RadarTrek score of 88/100 — a excellent result in the vector databases category. Scores above 75 indicate a tool that performs well across most dimensions without a critical weakness. At 88/100, Qdrant is a reliable choice for most teams evaluating this space. Scores are reviewed when significant updates are released, so the number reflects the current version of the product.
The best alternative to Qdrant depends on which dimension matters most to you. Use the "Compare with" links in the sidebar to see a head-to-head radar chart against any specific competitor in the vector databases category. The main vector databases category page ranks all tools by overall score and lets you filter by dimension to find alternatives that lead on your priority criterion.
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