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Cloudflare Vectorize vs Qdrant

Cloudflare Vectorize

developers.cloudflare.com

Qdrant

qdrant.tech

Side by side

FigureCloudflare VectorizeQdrant
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
WebYesYes
Windows—Yes
macOS—Yes
Linux—Yes
APIYesYes
Self-hosted—Yes
Plans published25
Spec score · Vector Databases8.0 (#8)8.0 (#9)
Spec score · Ai Databases7.9 (#17)8.0 (#14)
Founded20092021
HeadquartersSan Francisco, California, United StatesBerlin, Germany
ProductVectorize is a globally distributed vector database for building AI powered applications with Cloudflare Workers.Qdrant is a vector similarity search engine with an API to store, search, and manage vectors with additional payload data.
SupportCloudflare directs Vectorize users to its #vectorize Discord channel for questions, discussion, bug reports, and feedback.The pricing page lists community support as Discord-only and paid support options with 10h/day business-hours or 24/7 coverage.

Plans

Cloudflare Vectorize

  • Workers FreeFree
  • Workers PaidPrice not published

Cloudflare Vectorize pricing →

Qdrant

  • Free TierFree
  • Hybrid CloudPriced on request
  • Premium TierPriced on request
  • Private CloudPriced on request
  • Standard TierPriced on request

Qdrant pricing →

In their own words

Cloudflare Vectorize

Cloudflare Vectorize is a globally distributed vector database for AI applications built with Cloudflare Workers. It supports semantic search, recommendations, classification, anomaly detection, and supplying context to large language models. Vectors can come from Workers AI models or services such as OpenAI. Workers connect to indexes through a Vectorize binding configured in Wrangler or the Cloudflare dashboard, while a REST API can insert and query vectors. Search results can reference images in R2, documents in KV, and user profiles in D1. Metadata filters support indexed string, number, and boolean properties, with up to 10 metadata indexes per index. Each index can hold up to 20 million vectors, with a maximum of 1,536 dimensions at 32-bit precision. Queries return up to 50 results with values or metadata, or 100 without them. Cloudflare lists a free plan and paid usage from $5/mo. The Workers Free plan includes stated monthly queried and stored dimension allowances. Cloud deployment is available through API and web access.

Visit developers.cloudflare.com

Qdrant

Qdrant is a vector similarity search engine and API for storing, searching, and managing vectors with payload data. A point can pair a vector with JSON metadata that filters search results. It supports dense, sparse, and multivector configurations, plus hybrid retrieval that combines semantic and lexical search. These capabilities can serve semantic search and recommendation systems. Qdrant can run locally with its Docker image or through Qdrant Cloud. REST and gRPC APIs are available, along with official client libraries for Python, JavaScript/TypeScript, Rust, Go, .NET, and Java. Listed integrations include LangChain, LlamaIndex, Airbyte, Unstructured, DocArray, and AutoGen. The free cloud tier is intended for testing and prototypes, with a single-node cluster, 1GB RAM, and 4GB disk. Qdrant Cloud enables TLS and encryption at rest; self-hosted users must configure these controls, and authentication and encryption are off by default in self-hosted open-source deployments. Qdrant was founded in 2021 and is headquartered in Berlin, Germany.

Visit qdrant.tech