How to Choose a Vector Database — Graph vs. Integrated

AI Impact Summary

Vector databases are emerging as a critical component for modern applications leveraging machine learning, particularly for tasks like prompt retrieval for large language models. Choosing the right vector database is crucial, with options ranging from graph-based systems optimized for relationship analysis to integrated solutions. Key considerations include vector dimensions, search algorithms, and the database's ability to scale with data volume and integrate with existing systems, especially for efficient LLM prompt retrieval.