Milvus - Open Source Vector Database

Basic Information

• Product Name: Milvus
• Company/Organization: Zilliz (Commercial Company) / LF AI & Data Foundation (Open Source Foundation)
• Country/Region: USA/China
• Official Website: https://milvus.io/
• GitHub: https://github.com/milvus-io/milvus
• Type: Open Source Distributed Vector Database
• License: Apache 2.0
• Founded: 2019
• Cloud Service: Zilliz Cloud

Product Description

Milvus is an open-source distributed vector database designed for GenAI applications, hosted by the LF AI & Data Foundation. It supports vector data storage and search from millions to billions of vectors, offering multiple deployment options (Lite, Standalone, Cluster) and achieving ultimate performance through GPU acceleration. Zilliz is the commercial company behind Milvus, providing managed cloud services.

Core Features/Characteristics

• Multiple Similarity Metrics: Supports L2, IP, Cosine, and other distance calculations
• Hybrid Search: Combines vector search with scalar filtering
• Time Travel Query: Access historical data states
• GPU Acceleration: Built-in GPU index acceleration support
• Dynamic Schema: Flexible data model management
• Multi-Tenancy: Supports multi-tenant isolation
• Multiple Index Types: IVF, HNSW, DiskANN, etc.
• Distributed Architecture: Native support for horizontal scaling
• Multi-Language SDKs: Python, Java, Go, Node.js, etc.

Deployment Options

• Milvus Lite: Python library, suitable for local development and Jupyter Notebook
• Milvus Standalone: Single Docker image, complete database
• Milvus Cluster: Kubernetes cluster deployment, suitable for production environments
• Zilliz Cloud: Fully managed cloud service

Business Model

Open-source core + Zilliz Cloud managed services.

Pricing

• Open Source Edition: Free
• Zilliz Cloud Free: Up to 5GB storage
• Zilliz Serverless: 1536-dimensional vectors, ~$89/month for 1 million reads/writes
• Zilliz Dedicated: Starting from ~$114/month
• Billed based on storage, compute, and network usage

Target Users

• Large-scale AI application development teams
• Scenarios requiring GPU-accelerated search
• Enterprise-level distributed deployments
• Research institutions and academic projects

Advantages

• Truly distributed architecture, supporting billions of vectors
• GPU acceleration, extremely high performance
• Flexible deployment (from notebooks to clusters)
• Hosted by LF AI Foundation, large and active community
• Milvus Lite is ideal for local development

Limitations

• Full deployment (Cluster mode) is complex
• Relies on message queues like Kafka/Pulsar (Cluster mode)
• High resource consumption
• Steep learning curve

Relationship with OpenClaw

Milvus Lite can serve as a local vector storage solution for OpenClaw, providing API compatibility with Milvus Cluster, facilitating migration from local development to production environments. For OpenClaw enterprise deployments requiring large-scale knowledge bases, Milvus Cluster or Zilliz Cloud are reliable choices.

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