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Zilliz Cloud

Vector Database

The world’s most advanced managed vector database for high-performance AI and semantic search.

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About Zilliz

Zilliz is a high-performance vector database service built on Milvus. It is designed to store, index, and manage billions of embedding vectors generated by deep learning models for Generative AI and RAG applications.

How to Use

  1. 1. Create a cluster on Zilliz Cloud
  2. 2. Define your vector collection and schema
  3. 3. Connect via SDK (Python, Node.js, or Java)
  4. 4. Upsert vector embeddings from your AI models
  5. 5. Execute similarity searches with millisecond latency

Core Capabilities

⚡ Million-Scale Search
🛡️ SOC2 Compliance
⚙️ Auto-Scaling

Platform Specifications

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Primary Use Cases

Zilliz is essential for building Retrieval-Augmented Generation (RAG) systems, recommendation engines, image/video similarity search, and molecular discovery tools.

Performance & Latency

The database utilizes advanced indexing algorithms like HNSW and DiskANN to provide sub-second search results even across datasets containing billions of vectors.

Hybrid Search

Zilliz supports hybrid search capabilities, allowing users to combine vector similarity with traditional scalar filtering for more precise data retrieval.