An (Opinionated) Checklist to Choose a Vector Database | Pinecone

What this post added

This post introduces a structured framework for evaluating vector databases, detailing technical considerations such as data freshness, query latency, QPS, namespaces, accuracy, hybrid search (sparse-dense index), metadata filtering (single-stage), live index updates, horizontal/vertical scaling, and cost-efficiency. It also covers developer experience aspects like SDKs, documentation, and integrations, as well as enterprise readiness features like security, compliance, SLAs, and monitoring.