ZeusDB Vector Database

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ZeusDB is a high-performance vector database designed for storing, indexing, and searching the high-dimensional vector data used in AI and machine learning applications. It enables developers and data teams to build systems for semantic search, recommendation, similarity matching, retrieval-augmented generation (RAG), and other generative AI applications. ZeusDB is built for speed, reliability, and ease of integration with existing AI infrastructure. Key functionalities include: - Scalable Indexing Methods: Supports efficient similarity search at large scale using algorithms such as HNSW and Product Quantization (PQ). - Flexible Deployment: Can be deployed on-premises or in any cloud environment, providing control over your data infrastructure. - Advanced Search: Combines vector similarity search with metadata filtering for more precise and context-aware results. - Developer-Friendly API: Provides a robust and user-friendly Python API for flexible development and integration. - Enterprise-Grade Operations: Includes comprehensive logging, monitoring capabilities, and data persistence for production deployments. - Modern Pipeline Integration: Designed to integrate smoothly with modern data pipelines and MLOps workflows.