Qdrant

Qdrant is an open-source vector database written in Rust, first released in 2021 and known for high-performance HNSW indexing, rich payload filtering, and quantization options that dramatically reduce memory footprint. The platform supports binary, scalar, and product quantization that can compress vectors by 32x or more while preserving most recall accuracy, making it attractive for cost-sensitive RAG deployments. Qdrant offers self-hosted, cloud-managed, and hybrid-cloud options including a free in-memory mode for prototyping. Its filtering engine is unusually expressive, supporting complex boolean conditions, geo filters, and nested payload queries combined with vector search in a single request. AI governance teams appreciate Qdrant's Apache 2.0 licensing, Rust memory safety, and the absence of vendor lock-in, all of which support responsible AI vendor selection criteria. Notable adopters include Bayer, Disney, and many open-source RAG frameworks that ship Qdrant as a default vector backend for AI compliance reasons.

Qdrant + Centralpoint: Centralpoint integrates Qdrant under its model-agnostic governance layer, letting you take advantage of Qdrant's quantization to lower vector-storage cost while routing generation through whichever LLM you choose. Prompts stay local, tokens are metered per skill and audience, and Qdrant-backed chatbots deploy across portals with one line of JavaScript.


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