Hot Take: Vector Databases (Pinecone 1.11, Weaviate 1.26) Are Overhyped for Small-Scale RAG Workloads in 2026 The retrieval-augmented generation (RAG) hype cycle has pushed vector databases to the center of every AI stack. Managed options like Pinecone 1.11 and open-source stalwarts like Weaviate 1.26 are pitched as mandatory infrastructure for any RAG implementation. But for small-scale RAG workloads? They’re wildly overhyped. Defining Small-Scale RAG First, let’s set boundaries. Small-scale RAG here means: Fewer than 100,000 source documents (or ~500MB of raw text) Query volumes under 10 requests per second (QPS) Single-tenant, low-availability requirements (no SLA needs beyond basic uptime) Teams of 1-5 developers with no dedicated infrastructure staff If this describes your use case, the pitch for Pinecone 1.11 or Weaviate 1.26 falls apart quickly. 1. Cost Overhead You Don’t Need Pinecone 1.11’s free tier caps you at 1 index, 100k vectors, and no dedicated compute.…