The $1M Annual Cost of RAM-Bound Vector Databases in the Cloud

We analyzed the fundamental architectural flaw in today's cloud vector database paradigm: the hard dependency on RAM. This design forces platforms with massive data volumes (e.g., millions of video frames, billions of RAG documents) into a financially unsustainable cost curve. We propose that the shift to an O(k) architecture, leveraging mmap storage, is the only way to break this scaling ceiling.

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