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AI Tool Comparison

Qdrant vs Weaviate

A side-by-side breakdown to help you pick the right tool for your workflow.

Qdrant logo

Qdrant

Store and search embeddings at scale: self-host free and open source, or run managed Qdrant Cloud billed by infrastructure resources rather than per query.

Developer Tools
freemium
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Weaviate logo

Weaviate

Combine keyword and semantic search in one query, self-managed as open source or run on Weaviate Cloud with tiered SLAs.

Developer Tools
freemium
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Bottom Line

Last reviewed: August 2026

Qdrant and Weaviate both compete in Developer Tools, overlapping most directly on developer Tools. Qdrant carries the higher rating (4.6 vs 4.5), but a gap that size rarely overrides a real workflow fit on its own.

Choose Qdrant if…

Best for teams building production AI applications that need precise filtering alongside vector similarity search, and its edge is combines vector search with payload indexing, letting you filter results with real precision, not just approximate matches. A production-grade choice once you need that filtering control, self-hosting requires real ops knowledge to run well.

Choose Weaviate if…

Best for developers who want vectorization handled automatically at ingestion instead of a separate embedding step, and its edge is built-in integration with OpenAI, Cohere, and Hugging Face embedding providers, no manual vectorization pipeline. A genuinely batteries-included vector database, module configuration can get complex on advanced setups.

AttributeQdrantWeaviate
CategoryDeveloper ToolsDeveloper Tools
Pricingfreemiumfreemium
Pricing DetailFree (self-host) / Standard from ~$30-60/mo / Private Cloud $25K/yrFree (self-host) / Free tier Cloud / from $45/mo Flex
Rating4.64.5

Key Features

Qdrant

  • Fast Rust-based engine
  • Advanced payload filtering
  • Horizontal scaling
  • Managed cloud option

Weaviate

  • Built-in vectorizer modules
  • Hybrid (vector + keyword) search
  • Generative search
  • GraphQL and REST APIs

Pros

Qdrant

  • Excellent performance
  • Strong filtering
  • Production-grade

Weaviate

  • Batteries-included design
  • Strong hybrid search
  • Active community

Cons

Qdrant

  • Ops knowledge for self-host
  • Tuning needed at scale

Weaviate

  • Module config can be complex
  • Resource intensive

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