Weaviate

Weaviate is an open-source vector database that stores both data objects and their vector embeddings to enable semantic and hybrid search for AI applications.

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 by comparing the meaning encoded in vectors rather than relying solely on keyword matching. The database supports retrieval augmented generation workflows by providing context to generative models. It integrates with external model providers and offers an MCP server to allow LLMs and IDE assistants to interact with the database. Weaviate provides options for fully managed cloud deployment or self-deployment for development and production environments.

Weaviate at a glance

Best for: Software engineer
Runs on: API, self-hosted, open source
Pricing: Free tier for evaluation available; Weaviate Cloud options for development and production.
Released: March 2016
Category: AI coding tool
Website: weaviate.io

Key features

Semantic and hybrid search
Retrieval augmented generation support
Persistent memory for LLM agents
Integration with external model providers
Vector embedding storage and indexing
MCP server support for AI-assisted coding

Use it for

Building AI-powered applications
Powering agent-driven workflows
Implementing retrieval augmented generation
Enabling semantic search in applications

Companion to

Tools whose articles name Weaviate as a companion, each with its job for them.

Dify — Weaviate: Vector store

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