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Weaviate

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The open-source AI-native vector database built for production-scale search, RAG, and agents

Free tier available·All audiences·API available·Open source

Key strengths

Billion-scale vector search with multi-tenancy supportBuilt-in embeddings — no external pipeline requiredDeployment-agnostic: cloud, self-hosted, or on-premUnified platform for search, RAG, agents, and memory (Engram)Production-hardened with SOC 2, HIPAA, RBAC, and high availability
Free tier + paid plans
Amsterdam, Netherlands
Founded 2019
Self-hostable

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Developer Documentation

Weaviate offers comprehensive documentation across multiple surfaces — database, cloud, deployment, and agents — all available at weaviate.io/developers.

Key developer resources:

  • SDKs: First-class clients for Python, Go, TypeScript, and JavaScript, with idiomatic collection-based APIs.
  • APIs: Full GraphQL and REST API support for flexible querying and schema management.
  • Search modes: Pure vector (near_vector), semantic (near_text), and hybrid (vector + keyword with tunable alpha) search out of the box.
  • Multi-tenancy: Native tenant isolation allowing 50K+ segmented indexes within a single cluster — ideal for SaaS workloads.
  • Modules & integrations: Plug-in vectorizer modules (OpenAI, Cohere, HuggingFace, etc.) and integrations with AWS, Google Cloud, Snowflake, and Databricks.
  • Agents: Weaviate Agents Docs cover the Query Agent and upcoming agentic AI capabilities; LLM/Agent guides provide integration patterns.
  • Observability: Built-in observability, RBAC, SOC 2 & HIPAA compliance, and high-availability configurations for enterprise deployments.
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