Graph Databases for Generative AI

Graph databases have become a common starting point for generative AI applications, where large language models (LLMs) are used to talk to data. These databases allow users to store embeddings generated by LLMs in a vector database, enabling similarity searches. While vector databases are popular for their simplicity, graph databases offer the advantage of explicit relationships, which provide more accurate results. Combining the capabilities of both databases can enable a wide range of use cases, making them more relevant and accurate for enterprises.