Vector Database Selection for Enterprise LLM Applications

Author(s)	Prabu Arjunan
Country	United States
Abstract	Recent proliferation of LLMs in enterprise applications brings along an urgent need for efficient vector similarity search capabilities. This paper describes a comprehensive framework in selecting and implementing vector databases within the architecture of enterprise LLMs. This paper provides an in-depth analysis of the current solutions, real-world implementation patterns, and emerging trends to help organizations make informed decisions about their vector database infrastructure.
Keywords	Vector Databases, Large Language Models (LLMs), Enterprise Architecture, Vector Similarity Search, Retrieval Augmented Generation (RAG), HNSW, Approximate Nearest Neighbor Search, GPU Acceleration, Enterprise AI Infrastructure, Vector Search Optimization
Field	Engineering
Published In	Volume 4, Issue 12, December 2023
Published On	2023-12-06
Cite This	Vector Database Selection for Enterprise LLM Applications - Prabu Arjunan - IJLRP Volume 4, Issue 12, December 2023. DOI 10.5281/zenodo.14673081
DOI	https://doi.org/10.5281/zenodo.14673081
Short DOI	https://doi.org/g8z64f

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