Zilliz
Fully managed, scalable vector database for enterprise AI applications.
Please wait while we load the page
Zilliz provides a fully managed vector database management system, Zilliz Cloud, powered by the open-source Milvus. It is designed for enterprise-grade AI applications, supporting billion-scale vector search, Retrieval Augmented Generation (RAG), and large language models. Zilliz aims to simplify the deployment and scaling of vector search applications by eliminating the need for complex infrastructure management.
To use Zilliz Cloud, users can sign up for a free account, download one of the official SDKs (Python, Java, Go, Node.js), create their first collection, and perform vector similarity searches. For launching applications, users can upgrade to a pay-as-you-go plan. The platform offers intuitive RESTful APIs and user-friendly SDKs for control and data plane operations.
You should go with Zilliz if you need a powerful, fully managed vector database that scales big and fast. It’s perfect for AI apps needing billion-scale search and integrates smoothly with cloud providers, so you can focus on building without sweating infrastructure headaches.
A starting point for learning, experimenting, and prototyping, with easy migration to paid plans. Includes 5 GB storage (enough for 1M 768 dim vectors), 2.5M vCUs per month, and up to 5 collections. Serverless.
Pay only for what you use. Auto-scaling. Up to 100 collections. For applications with variable or infrequent traffic. Minimal configuration required.
Dedicated clusters offer use case optimized CUs to achieve high control, consistent performance, and cost-effectiveness. Suitable for development and testing. Includes multiple cloud providers and regions, use case optimized CU types, and basic metrics and monitors. Up to 30-day free trial available.
Designed for organizations prioritizing custom infrastructure, enhanced data protection, and compliance. Deploy on your infra of choice with enhanced data control and security, and flexibility and scalability on demand.