Building Vectorize, a distributed vector database, on Cloudflare’s Developer Platform

Cloudflare details the design and operation of Vectorize, a globally distributed vector database that uses IVF indexing, Product Quantization, and approximate nearest neighbor search with refinement to deliver fast, accurate vector similarity queries at scale. The post explains snapshot-based eventual consistency, a WAL-coordinated asynchronous write pipeline leveraging Durable Objects, executors, and trainers for retraining generations, as well as metadata filtering via chunked sorted lists. It highlights performance strategies (caching, SIMD, binary formats, fragmentation), horizontal scalability across data centers, and increased limits up to 5M vectors, positioning Vectorize for high-throughput, low-latency AI and semantic search applications.