Zilliz Cloud is a fully managed vector database platform built on the open-source Milvus® engine. It is designed to unlock the full potential of unstructured data for AI applications, offering high-performance, scalable, and secure vector search capabilities. Zilliz Cloud supports multimodal data, including text, image, and audio embeddings, and is optimized for use cases such as recommendation systems, retrieval-augmented generation (RAG), and anomaly detection. The platform provides a cloud-native architecture with distributed scalability, automated indexing, and intelligent query optimization. It eliminates the need for manual tuning and infrastructure management, allowing developers to focus on building innovative AI solutions.

Features

• AutoIndex & Cardinal Search Engine: AI-powered indexing combining IVF and graph techniques for optimal performance.
• Smart Query Optimizer: Automatically selects the best algorithm for each dataset to maximize accuracy and speed.
• Optimization Suite: End-to-end performance tuning across algorithms, systems, and hardware.
• Tiered Storage: Automated storage tiering for cost-effective performance.
• Multi-Cloud Deployment: Available on AWS, Azure, and Google Cloud with flexible deployment options including BYOC (Bring Your Own Cloud).
• Enterprise-Grade Security: Strong defaults, private networking, and robust operational controls.
• Hybrid Search: Supports multimodal queries across sparse-dense and dense-text combinations.
• Similarity Metrics: Offers Cosine, Euclidean, Inner Product (IP), and more for flexible search strategies.
• Tunable Consistency: Multiple consistency levels to balance accuracy and performance.
• Low Latency & High Recall: Real-time decision-making with sub-second response times.
• Horizontal Scalability: Component-based architecture for dynamic scaling.

Benefits

• Reduced TCO: Up to 70% lower total cost of ownership compared to self-hosted Milvus deployments.
• Operational Efficiency: Eliminates manual infrastructure management and performance tuning.
• Developer Productivity: Streamlined APIs and automated deployment accelerate development cycles.
• Scalability & Reliability: Handles millions of high-dimensional vectors with sub-300ms latency.
• Security & Compliance: Enterprise-grade security ensures data protection across cloud environments.
• Flexibility: Supports diverse AI workloads and adapts to changing data and performance needs.
• Customer Success: Trusted by leading AI companies for multilingual RAG systems, recommender engines, and hybrid search.