Welcome to Weaviate Docs

Weaviate (we-vee-eight) is an open-source, AI-native vector database. Use this documentation to get started with Weaviate and learn how to get the most out of Weaviate's features.

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Start with the Quickstart tutorial – an end-to-end demo that takes 15–30 minutes.

Find the right documentation and resources

The Weaviate documentation is structured into multiple units based on the service and functionality.

Weaviate Database

Develop AI applications using Weaviate's APIs and tools

Deploy

Deploy, configure, and maintain Weaviate Database

Weaviate Agents

Build and deploy intelligent agents with Weaviate

Weaviate Cloud

Manage and scale Weaviate in the cloud

What is Weaviate?

Weaviate is an open-source vector database designed to store and index both data objects and their vector embeddings. This architecture enables advanced semantic search capabilities by comparing the meaning encoded in vectors rather than relying solely on keyword matching. Key capabilities include:

Semantic and hybrid search
By indexing data with vectors, Weaviate supports searches based on both semantic similarity and keywords. This allows for more relevant results even when the query terms don’t exactly match the stored data.
Retrieval augmented generation (RAG)
Weaviate can serve as a robust backend for RAG workflows, where vector search is used to retrieve context that enhances the output of generative models, making it easier to generate accurate, context-aware responses.
Agent-driven workflows
Its flexible API and integration with modern AI models make Weaviate suitable for powering applications that rely on intelligent agents. These agents can leverage semantic insights to make decisions or trigger actions based on the data stored in Weaviate.

The Weaviate Ecosystem

The Weaviate ecosystem consists of multiple tools and services centered around building cloud-native AI-powered applications.

As shown in the high-level overview above, the ecosystem consists of:

Weaviate Database: An open source vector database that stores both objects and vectors.
Weaviate Cloud: A fully managed cloud deployment of the Weaviate vector database.
Weaviate Agents: Pre-built agentic services for Weaviate Cloud users.
Weaviate Embeddings: A managed embedding inference service for Weaviate Cloud users.
External model providers: Third-party models that integrate with Weaviate.