Icon of Zilliz Cloud: Enterprise-Level Vector Database Powered by MilvusZilliz Cloud

Zilliz Cloud - Zilliz Cloud: Enterprise-Level Vector Database Powered by Milvus

Zilliz Cloud is the leading enterprise-level vector database service, built on the powerful open-source Milvus platform. It delivers high performance, reliability, and scalability for AI applications, all without the complexity of infrastructure management.

Zilliz Cloud Product Information

What is Zilliz Cloud?

Zilliz Cloud provides a fully-managed Milvus service that simplifies the deploying and scaling of vector search applications. As the creators of Milvus, Zilliz Cloud ensures an optimized AUTOINDEX balancing recall and performance, 10x faster vector retrieval speed with the Cardinal search engine, and multi-cloud support on AWS, Azure, and GCP across eight regions worldwide.

How to Use Zilliz Cloud?

Sign up for a free Zilliz Cloud account, grab one of the official SDKs, and start by creating your first collection for vector similarity search. When your application is ready for launch, upgrade to a pay-as-you-go plan to leverage the high performance, reliability, and scalability capabilities of Zilliz Cloud.

Core Features of Zilliz Cloud

  • High performance and reliability
  • Fully managed service
  • Optimized AUTOINDEX
  • 10x faster vector retrieval speed
  • High scalability and multi-cloud support
  • Built-in embedding pipelines
  • AI model integrations

Use Cases of Zilliz Cloud

  • AI applications requiring vector similarity search
  • Incorporating external data sources into LLMs and AI applications
  • Recommendation systems based on user behaviors and preferences
  • Searching for similar texts, images, audio, and videos
  • Interactive QA chatbots and molecular similarity search
  • Multimodal similarity search across different modalities

FAQ about Zilliz Cloud

Where can vector databases help?

Vector databases are essential for expanding LLMs' knowledge, recommendations based on user behaviors, similarity search for texts, images, audio, and videos, interactive QA chatbots, molecular similarity search, and multimodal similarity search.

Want to learn more about vector databases?

Explore our guide on Vector Databases to understand the paradigm shift needed in handling unstructured data and how it relates to the emergence of Vector Databases.

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