Vector Databases

Qdrant vs Weaviate.

Both sit in Vector Databases, scored on the same six pillars from the same published methodology. Here is where they actually differ.

The short answer

Too close to call on score alone — Qdrant sits at 81.0 and Weaviate at 81.9. A gap that size is inside the noise of any honest scoring model, so pick on fit rather than rank.

Qdrant leads on value for money; Weaviate leads on maturity & reliability.

Qdrant

Qdrant Solutions

81.0

Strong

Rust-powered open-source vector search engine tuned for performance.

From
Free (self-hosted) / Cloud free 1GB tier
Pricing
Open Source
Maturity
Established
Founded
2021
Weaviate

Weaviate B.V.

81.9

Strong

Open-source AI-native database with hybrid search and modular vectorizers.

From
Free (self-hosted) / Cloud from $25 per month
Pricing
Open Source
Maturity
Established
Founded
2019

Pillar by pillar

The same six pillars and fixed weights used for every tool on the site. A lead of fewer than 5 points is not called for either side — these are evidence-backed judgements, not measurements. Read the methodology.

Capability

Level

Qdrant81
Weaviate82

Value for Money

Qdrant by 5

Qdrant90
Weaviate85

Security & Compliance

Level

Qdrant78
Weaviate82

Integrations & Ecosystem

Level

Qdrant82
Weaviate86

Maturity & Reliability

Weaviate by 5

Qdrant75
Weaviate80

Momentum

Level

Qdrant78
Weaviate76

Which one, and when

Pick Qdrant if

  • cost per unit of output is the binding constraint — it leads Value for Money by 5 points.
  • Performance-critical vector search
  • Budget-conscious startups
  • Self-hosted deployments

The catch

  • Smaller managed-cloud track record than Pinecone
  • Fewer built-in embedding integrations than Weaviate modules
Full Qdrant profile →

Pick Weaviate if

  • it has to hold up in production from day one — it leads Maturity & Reliability by 5 points.
  • Hybrid search applications
  • SaaS multi-tenant vector workloads
  • Teams wanting open source + cloud option

The catch

  • Operating large self-hosted clusters requires expertise
  • GraphQL API adds a learning curve
Full Weaviate profile →

What each is good at

Qdrant

  • Excellent performance-per-dollar; Rust core with low memory footprint
  • Advanced quantization (binary, scalar, product) cuts costs dramatically
  • Simple, well-documented API loved by developers

Weaviate

  • True open source with a first-class managed cloud
  • Native hybrid (BM25 + vector) search and reranking
  • Multi-tenancy designed for SaaS builders

Other comparisons in Vector Databases

Comparing something else? Build your own side-by-side across any tools in the catalog.