zilliztech/attu

The Best GUI for Milvus

What it solves

Attu provides a visual management interface for Milvus vector databases, eliminating the need to interact with the database solely through code or CLI. It simplifies complex operations like browsing collections, performing vector searches, and monitoring cluster health across multiple environments (dev, staging, production) from a single instance.

How it works

Attu acts as a management layer that connects to Milvus clusters via gRPC. It offers a web-based or desktop application that allows users to to browse data, manage schemas, and perform searches. It includes a built-in AI agent that can execute database management tasks using natural language commands and integrates with various embedding providers (OpenAI, Cohere, Jina, etc.) to facilitate interactive vector similarity searches.

Who it’s for

It is designed for AI engineers, database administrators, and data scientists who use Milvus for vector storage and retrieval, and who need a GUI for data exploration, cluster monitoring, and administrative tasks.

Highlights

  • Multi-Cluster Management: Manage multiple Milvus instances from one deployment.
  • AI Agent: Chat-driven management with over 50 tools for creating collections and analyzing performance.
  • Data Explorer: Inline editing and import/export support for CSV, JSON, and Parquet formats.
  • Cluster Monitoring: Real-time health checks and Prometheus metrics with interactive topology visualization.
  • Backup & Restore: Full and incremental backups supporting S3, MinIO, GCS, and Azure Blob Storage.
  • Advanced Search: Support for hybrid search, MinHash deduplication, and Function Score reranking.

Related

  • Project
    milvus-io/milvus

    Milvus is a high-performance, distributed vector database built for scaling AI applications that require efficient search and organization of massive amounts of unstructured data.

  • Project
    milvus-io/milvus-lite

    Milvus Lite is a pure‑Python, local‑only version of the Milvus vector database. It provides a drop‑in `pymilvus`‑compatible API for storing dense and sparse vectors, scalar fields, and full‑text data, and supports similarity search, filtering, and hybrid (vector + text) queries. Designed for notebooks, tests, and small prototypes, it runs either as a local `.db` file, an embedded engine, or a lightweight gRPC server, and can later be swapped to a full Milvus deployment with minimal code changes.

  • Project
    milvus-io/milvus-sdk-java

    The Milvus Java SDK is the official Java client for the Milvus vector database, letting Java developers connect to and use Milvus from their applications.

  • Project
    milvus-io/pymilvus

    A Python SDK for Milvus, providing a programmatic interface to manage and search high-dimensional vector embeddings in the Milvus vector database.

  • Project
    RizRiyz/luvus

    Luvus is a cross‑platform terminal UI that lets you launch, monitor, and orchestrate AI coding agents (Claude, Codex, Grok, etc.) alongside shells, editors, and Git tools. It provides persistent workspaces, pane management, agent‑aware status panels, Git/GitHub integration, remote‑machine support, a read‑only web view, and an extensible module system. Install via a script, Homebrew, or PowerShell, then use `luvus` to start a session, `luvus doctor` to verify setup, and `luvus update` for upgrades.