Graph databases are exploding, thanks to the AI boom - here's why

The article discusses the rising popularity of graph databases, driven by the increasing demand for complex data-processing capabilities in artificial intelligence (AI) applications. Graph databases excel at handling interconnected data, making them well-suited for AI systems that require the analysis of intricate relationships and patterns within large, unstructured datasets. As AI applications become more data-intensive, traditional relational databases often struggle to keep up, leading to the growing adoption of graph databases. These specialized databases are designed to efficiently store and query data organized as nodes (entities) and edges (relationships), allowing for faster and more intuitive exploration of complex data structures. The article highlights the pivotal role that graph databases and knowledge graphs play in powering AI-driven applications, such as recommendation systems, knowledge management, and natural language processing. This surge in demand for graph-based data management solutions is expected to continue as the AI industry continues to expand, fueling further innovation and advancements in this field.