Multi-engine data platform architecture for data virtualization
In today's AI-driven environment, the urgency to gather data from various sources and generate real-time insights has never been more critical. This need has prompted the development of a Multi-Engine Data Virtualization Framework, an innovative strategy crafted to enhance data virtualization and management. Unlike traditional data virtualization systems that struggle with complex and large-scale data, this new framework seeks to leverage the unique strengths of different data platforms to improve data virtualization's efficiency and effectiveness. It addresses common data management challenges by enabling smooth integration of federated queries across multiple data engines. The framework explores caching databases, massively parallel processing (MPP) engines, and vector databases to facilitate real-time analytics.