arXiv · 2503.04847
Role of Databases in GenAI Applications
Abstract
Generative AI (GenAI) is transforming industries by enabling intelligent content generation, automation, and decision-making. However, the effectiveness of GenAI applications depends significantly on efficient data storage, retrieval, and contextual augmentation. This paper explores the critical role of databases in GenAI workflows, emphasizing the importance of choosing the right database architecture to optimize performance, accuracy, and scalability. It categorizes database roles into conversational context (key-value/document databases), situational context (relational databases/data lakehouses), and semantic context (vector databases) each serving a distinct function in enriching AI-generated responses. Additionally, the paper highlights real-time query processing, vector search for semantic retrieval, and the impact of database selection on model efficiency and scalability. By leveraging a multi-database approach, GenAI applications can achieve more context-aware, personalized, and high-performing AI-driven solutions.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Santosh Bhupathi. 2025-03-05. Role of Databases in GenAI Applications. https://arxiv.org/abs/2503.04847
Cite the original work for its findings. Save a collection to share your selection of sources.