Cloudflare Vectorize review
A focused vector database for Workers apps with simple pricing and metadata-aware search.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Cloudflare Vectorize is a managed, globally distributed vector database for storing and querying machine-learning embeddings. It is designed for applications built with Cloudflare Workers, including semantic search, recommendations, classification, anomaly detection, and retrieval-augmented generation. Developers can insert or upsert vector records, store metadata alongside vectors, filter by metadata, use namespaces for partitioning, and query or retrieve vectors by identifier. Cloudflare Workers bindings and API access support applications that keep their data and AI services within the Cloudflare ecosystem.
Pricing is structured around Workers plans. The Workers Free plan includes 30 million queried vector dimensions per month and 5 million stored vector dimensions. Workers Paid costs $5 per month, with a minimum account charge of $5, the first 50 million queried vector dimensions included, and the first 10 million stored vector dimensions included. Additional queried and stored dimensions are billed by usage. This gives small Workers projects a low-cost entry point while making usage volume the main pricing variable as an application grows.
Vectorize fits best when a project needs dense-vector similarity search alongside straightforward metadata and namespace controls. Integrations with Cloudflare Workers AI, R2, KV, D1, and OpenAI support common embedding, storage, and application workflows. Its focus is narrower than systems that combine dense, sparse, or hybrid retrieval: vectors support a maximum of 1,536 dimensions, and hybrid and sparse-vector search are not part of the listed capability set. Choose Vectorize for Cloudflare-native applications that value simple vector CRUD and filtering; choose an alternative when advanced retrieval modes or higher-dimensional vectors are central requirements.
Cloudflare Vectorize pros and cons
- Where it wins
- Free Workers tier with vector query and storage allowances
- Metadata filtering, namespaces, and configurable distance metrics
- Native integrations with Workers, Workers AI, R2, KV, and D1
- Where it doesn't
- Maximum vector dimensionality is 1,536 dimensions
- No verified hybrid or sparse-vector search capabilities
- Paid usage adds charges beyond included query and storage allowances
Cloudflare Vectorize fact sheet, pricing and score →
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