卓越
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Edge-native managed vector database integrated with Cloudflare Workers. Supports 50,000 namespaces and up to 5M vectors per index for low-latency applications.

Managed edge database using SQLite with sqlite-vec for per-tenant vector stores. Provides isolation via one database per tenant, suitable for edge deployments.

Resource-efficient on-device vector database with sync for mobile/IoT/embedded, enabling low-latency offline AI vector ops without cloud. Supports edge-first apps; more efficient than server-based Qdrant.

Compact 2MB standalone database for low-latency vector search on IoT/mobile/embedded, no server needed for on-device real-time AI ops.

Edge-native vector database enabling sub-15ms ANN queries on remote devices without cloud dependency, using efficient disk-based indexing for real-time processing. Supports offline operation with synchronization capabilities, optimized for low-resource environments. Ideal for edge RAG, facial recognition, and IoT recommendations; more compact than Milvus for disconnected setups, edge-focused unlike Qdrant's distributed architecture.

Cloudflare's globally-distributed vector database running on their edge network. Provides low-latency vector search with automatic global replication and serverless pricing starting at $0.31/month.

WASM bindings for RuVector vector database, enabling browser and edge runtime vector search and storage.

Lightweight embedded vector database for RAG systems useful in edge environments, running directly on devices with local vector search and no network latency or cloud dependencies.

A high-performance embedded database for edge devices and mobile, offering vector search capabilities for AI applications.