Qdrant vs Weaviate

Qdrant is freemium — a usable free tier with paid plans above it. Weaviate is freemium — a usable free tier with paid plans above it. Both are listed under Vector Databases & RAG Infra, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.

Qdrant vs Weaviate — straight answers

Qdrant vs Weaviate: what is the difference?

Qdrant is freemium — a usable free tier with paid plans above it and is listed for open-source Rust-based vector database, self-hostable for free with no scale limit. Weaviate is freemium — a usable free tier with paid plans above it and is listed for free managed cloud plan (100k objects, 1GB memory, 10GB disk) to explore without self-hosting. Both sit in Vector Databases & RAG Infra.

Is Qdrant or Weaviate cheaper to start with?

Neither — Qdrant and Weaviate are both freemium, so the choice comes down to capability rather than cost. Both entries list what they uniquely do above.

Which should I choose, Qdrant or Weaviate?

Choose Qdrant if you need open-source Rust-based vector database, self-hostable for free with no scale limit; choose Weaviate if you need free managed cloud plan (100k objects, 1GB memory, 10GB disk) to explore without self-hosting. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

Qdrant compared with Weaviate: pricing tier, category, listed capabilities and links.
 QdrantWeaviate
Pricing tierFree tier + paid plansFree tier + paid plans
Free to startYesYes
CategoryCode & DevelopmentCode & Development
TypeVector Databases & RAG InfraVector Databases & RAG Infra
Listed capabilities
  • Open-source Rust-based vector database, self-hostable for free with no scale limit
  • Managed free tier cluster (0.5 vCPU/1GB RAM/4GB disk) for prototyping RAG apps with no card required for OSS use
  • Hybrid Cloud option to run managed clusters on your own infrastructure for compliance-sensitive RAG
  • Free managed cloud plan (100k objects, 1GB memory, 10GB disk) to explore without self-hosting
  • Open-source core project can be self-hosted for free indefinitely, same engine as the managed cloud
  • Built-in hybrid (vector + keyword) search and native embedding/query-agent integrations
Tagsqdrant, vector database, rag infrastructure, open source vector db, free tier, embeddings searchweaviate, vector database, rag infrastructure, open source, free tier, hybrid search
Websiteqdrant.techweaviate.io
Full pageQdrant details →Weaviate details →
AlternativesQdrant alternatives →Weaviate alternatives →

Vespa

Vector Databases & RAG Infra
freeNew
  • Open-source AI search platform combining vector, text and structured search
  • Real-time indexing and on-node ML inference
  • Apache-2.0; free to self-host

LanceDB

Vector Databases & RAG Infra
freeNew
  • Embedded, developer-friendly retrieval library for multimodal AI
  • Columnar Lance format with vector and full-text search
  • Apache-2.0

Microsoft GraphRAG

Vector Databases & RAG Infra
freeNew
  • Builds knowledge graphs and community summaries from private text for RAG
  • Answers global, dataset-wide questions that vector RAG misses
  • Open-source Python library and CLI
  • Works with OpenAI-compatible and local models

Milvus

Vector Databases & RAG Infra
freeNew
  • Cloud-native Apache-2.0 vector database for large-scale similarity search
  • Runs from a single-file Lite mode to distributed clusters
  • Managed Zilliz Cloud has a separate free tier

pgvector

Vector Databases & RAG Infra
freeNew
  • Open-source vector similarity search extension for Postgres
  • HNSW and IVFFlat indexes with exact and approximate search
  • Available on most managed Postgres hosts

txtai

Vector Databases & RAG Infra
freeNew
  • All-in-one embeddings database for semantic search, LLM orchestration and workflows
  • Runs fully local with open models
  • Apache-2.0