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Title	pgvector vs Pinecone vs Qdrant — Who Wins the Vector DB Battle for LLMs?
URL	https://agixtech.com/vector-database-open-source-llms/
Category	Internet --> Blogs
Meta Keywords	#ragsystems #vectorsearch #pgvector #pinecone #qdrant #largelanguagemodels #mistral #ollama #selfhosted #aiengineering #agixtechnologies
Meta Description	We compared PostgreSQL + pgvector, Pinecone, and Qdrant to see which performs best for self-hosted LLM apps, private AI deployments, and enterprise-grade retrieval workflows.
Owner	Eric Weston
Description
Building RAG for LLaMA, Mistral, or Ollama? Then choosing the right vector database isn’t optional — it’s mission-critical for speed, recall accuracy, and long-term scalability. In this breakdown, we compare PostgreSQL + pgvector, Pinecone, and Qdrant across real production criteria like: ⚡ Query latency & throughput ???? Memory footprint & embeddings scale ????️ Hybrid search & metadata filters ????️ Open-source flexibility vs managed simplicity ???? Cost efficiency for real-world LLM workloads Whether you're deploying private AI apps, enterprise RAG, or secure on-prem LLM systems, this guide helps you choose the right backbone for your vector search stack.