In today’s rapidly evolving digital landscape, vector databases are emerging as a key enabler for enterprises looking to harness the potential of unstructured data, particularly in the realm of agentic AI. As organizations generate vast amounts of unstructured data, traditional databases struggle to process and query this information effectively. Vector databases provide a solution by representing data as high-dimensional vectors, allowing for more efficient search, retrieval, and analysis. This report explores vector databases’ role in the modern AI ecosystem, examining their impact on unstructured data management, their comparison with traditional databases, and their growing adoption across industries. It highlights their importance in powering AI-driven applications such as personalization, recommendation systems, and vector search. The report also discusses the challenges enterprises face in adopting these technologies, the evolving supplier landscape, and the future of vector databases as they continue to be essential in digital transformation. Scope All industries and geographies Contents In this report, we examine: Vector databases against traditional databases Their role in generative AI implementations Their current adoption and supplier landscape The adoption challenges enterprises face Emerging trends in the vector database management system market The way forward with vectors