Dev Tools · 2h ago
Building a RAG System: pgvector vs Dedicated Vector DBs
This article explains design decisions for a RAG system using pgvector, Gemini embeddings, and HNSW indexing. It covers trade-offs like 768 vs 3072 dimensions and asymmetric task types for retrieval. The author argues pgvector is sufficient for most enterprise use cases until hitting scale limits.
Meridian48 take
A practical guide that demystifies RAG architecture choices, though it assumes familiarity with vector databases and may oversimplify migration triggers.
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Building a RAG System from Scratch — Design Decisions Explained →
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