Vald is a unique numerical vector search engine designed and implemented on a cloud-native architecture. It fully utilizes the high-speed search capabilities of the fastest approximate nearest neighbor (ANN) algorithm, NGT, to construct a highly scalable distributed system. This design enables Vald to provide stable and rapid solutions when handling large, complex, and frequently changing datasets.
As an exceptional developer tool, Vald meets the diverse and complex query needs with its high scalability and flexibility. Whether for real-time search, recommendation systems, or vector retrieval in machine learning, Vald offers efficient solutions. At the same time, its powerful features do not add complexity to its use. Thanks to its cloud-native architecture, it can easily integrate with existing services and supports containerized deployment, significantly simplifying operation and management in diverse environments.
Additionally, Vald provides vector database services in the form of a data model. This structure allows a wide variety of data and information to be effectively stored and retrieved, further enhancing its practicality in big data processing and machine learning applications. With its comprehensive and diverse features and strong scalability, Vald has become an essential tool for AI developers and researchers.
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