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Vector Databases comparison · 2026
Weaviate (86) and Qdrant (88) are closely matched — this is one of the tightest Vector Databases comparisons in our database, with just 2 points separating them overall. The two are closest on Developer UX, where the gap is just 3 points. Both offer a free tier, making either a low-risk starting point. Use the radar chart and dimension table below to find which fits your specific priorities best.
Weaviate
Open-source vector database with built-in hybrid search
86/100
Qdrant
Fast, open-source vector search written in Rust
88/100
Radar comparison
Weaviate
86
Qdrant
88
Developer UX
SDK quality, indexing API, and setup speed.
Query Performance
ANN search speed and recall accuracy at scale.
Scalability
Index size limits and horizontal scaling for billions of vectors.
Price / Value
Cost per million vectors and free tier generosity.
Hybrid Search
Combining vector similarity with keyword/metadata filtering.
Ecosystem
LangChain/LlamaIndex integrations and framework support.
Overall Score
Based on our independent scoring across 6 dimensions, Qdrant scores 88/100 overall versus Weaviate's 86/100 — a 2-point margin. Qdrant leads on Hybrid Search in particular. That said, Weaviate may still be the right choice if the dimensions where it scores higher match your specific priorities — the radar chart above shows the full profile side by side.
Both Weaviate and Qdrant offer a free tier, so entry-level cost is not a differentiating factor. Compare the feature and usage limits of each free plan to see which gives you more headroom before a paid upgrade is needed.
Weaviate and Qdrant are closely matched across all dimensions. Weaviate has a slight edge on Hybrid Search — choose it if those align with your priorities. Qdrant scores marginally better on Price / Value — choose it if those are more relevant to your use case. The radar chart above shows the full comparison at a glance.
Switching between vector databases tools is generally possible but involves migration effort: exporting your data or configuration from Weaviate, re-importing or reconfiguring in Qdrant, and updating any API integrations or environment variables in your codebase. The effort scales with how deeply embedded the tool is in your stack. Test Qdrant on a non-production project first before migrating.
Weaviate (86/100) is the better fit for teams who prioritise hybrid search — its strongest dimension — and who want a free entry point. Qdrant (88/100) is the better fit for teams who prioritise query performance and want a free entry point. If both dimensions matter equally, the overall score winner (Qdrant) is the safer default choice.
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