4 min read
Embedding Models: Which One, and Why It Matters Less Than You Think
Embedding model choice is a 5% problem for most RAG systems. Your chunking strategy is the 50% problem. Here's how to pick anyway.
Tag
3 posts on Vector Search
Embedding model choice is a 5% problem for most RAG systems. Your chunking strategy is the 50% problem. Here's how to pick anyway.
LLMs don't know your data. RAG fixes that by turning your documents into a searchable knowledge base. Here is the full pipeline: chunking strategies, dense vs hybrid retrieval, re-ranking, and when to reach for graph-based RAG with LightRAG.
Pinecone, Weaviate, Milvus, pgvector, Qdrant — five viable choices for a vector database. Here is why I picked Qdrant for production, how the 3-node cluster is laid out, and what the other options actually trade away.