Weaviate Database
Weaviate (we-vee-eight) is an open-source, AI vector database. Use this documentation to get started with Weaviate and learn how to get the most out of Weaviate's features.
New to Weaviate?
Start with the Quickstart tutorial – an end-to-end demo that takes 15–30 minutes.
Weaviate Academy
Check out Weaviate Academy – a learning platform centered around AI-native development.
Find the right documentation and resources
Section titled “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
Query Agent
Run agentic search over your Weaviate Cloud collections
Weaviate Cloud
Manage and scale Weaviate in the cloud
Engram
Persistent memory for LLM agents and applications
AI-assisted coding
Section titled “AI-assisted coding”Check out our resources on AI-assisted coding (Vibe coding) with Weaviate:
Weaviate MCP Server
Enable and configure the Weaviate MCP server so LLMs and IDE assistants can interact with your Weaviate instance.
Best practices for coding with AI
Avoid hallucinations and improve your AI-assisted coding experience.
What is Weaviate?
Section titled “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:
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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.
Key Concepts & Architecture
Become familiar with Weaviate's architecture, core concepts, and key capabilities. Understand how its features and integrations map to AI builders' needs.
The Weaviate Ecosystem
Section titled “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.
- Query Agent: A pre-built agentic search service 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.
Choose your deployment
Section titled “Choose your deployment”Weaviate Cloud
- From evaluation (free tier) to production
- Shared Cloud (infrastructure managed by Weaviate)
- (Optional) Data replication (high-availability)
- (Optional) Zero-downtime updates
Set up a WCD instance
Docker
- For local evaluation & development
- Local inference containers
- Multi-modal models
- Customizable configurations
Run Weaviate with Docker
Kubernetes
- For development to production
- Local inference containers
- Multi-modal models
- Customizable configurations
- Self-deploy or Marketplace deployment
- (Optional) Zero-downtime updates
Run Weaviate with Kubernetes
Embedded Weaviate
- For basic, quick evaluation
- Conveniently launch Weaviate directly from Python or JS/TS
Run Embedded Weaviate
Community & Support
Section titled “Community & Support”Get help, share what you're building, and connect with the Weaviate community and team.
Community Forum
Ask technical questions, get help with your cluster, and connect with other developers and the Weaviate team. Open to everyone and a great place to start.
Support
Weaviate Cloud user or customer? The Support page explains all the ways to get help from the Weaviate team.
Open-source on GitHub
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