← Back to Directory

Weaviate

LLM Orchestrators

Overview

An open-source vector database that allows developers to store data objects and vector embeddings from their favorite ML models. It features hybrid search and integrated multi-modal capabilities.

Weaviate is an open-source vector database with hybrid (vector + keyword) search and multimodal support, letting teams store objects and embeddings together. It is flexible, self-hostable, and offers a managed cloud. It targets developers building AI search and RAG systems who want openness and hybrid retrieval.

Key Features

  • Open-source vector database
  • Hybrid vector + keyword search
  • Multimodal capabilities
  • Self-hosted or managed cloud
  • GraphQL and REST APIs

Best For

Developers who want an open, hybrid-search vector database for AI search and RAG.

Pros & Cons

Pros
  • Open-source and flexible
  • Strong hybrid search
  • Self-host or cloud
Cons
  • Self-hosting needs ops
  • Tuning required for scale
Advertisement

Pulse Verdict

The versatile vector powerhouse. Weaviate's open-source nature and hybrid search capabilities make it a top choice for developers building complex AI search systems.

Pricing

Open-source self-host; managed cloud billed by usage.

Pricing changes often — confirm current plans on the official site.

Visit Official Website →

Related Tools

Pinecone

The industry-leading managed vector database designed for high-performance AI applications. It provides the long-term memory needed for RAG pipelines and autonomous agents.

Qdrant

A high-performance vector similarity search engine and database. It provides a production-ready service with a user-friendly API for storing and searching high-dimensional vectors.

See Weaviate Compared

Infrastructure
Best AI Vector Databases 2026: Pinecone vs Weaviate vs Qdrant

Master AI Automation 2026 and Generative Engine Optimization. Comparing Pinecone, Weaviate, and Qdrant for high-performance RAG and enterprise semantic search.