Weaviate
Free tierThe open-source AI-native vector database built for production-scale search, RAG, and agents
Free tier available·All audiences·Powered by Snowflake, ModernBERT (via Weaviate Embeddings); external LLMs connectable·API available·Open source
Key strengths
Open-source vector databaseBillion-scale architectureBuilt-in embeddings (no external pipeline required)Hybrid search (vector + keyword)Multi-tenancyDeployment-agnostic (cloud or self-hosted)RAG and agentic AI supportSOC 2 Type II and HIPAA compliance
Free tier + paid plans · from $45 USD/mo
Amsterdam, Netherlands
Founded 2019
Self-hostable
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Weaviate — Technical Overview
Weaviate is an open-source vector database (16,892 GitHub stars) purpose-built for AI-native applications at any scale. It provides a fully managed cloud offering alongside self-hosted deployment options, giving engineering teams complete flexibility over their infrastructure.
Core architecture highlights:
- Hybrid search engine combining dense vector search with BM25 keyword search in a single query pipeline
- Built-in embeddings via Weaviate Embeddings (powered by Snowflake and ModernBERT models), eliminating the need for an external vectorization pipeline
- Billion-scale architecture with native multi-tenancy for workload isolation
- Deployment-agnostic — run on Weaviate Cloud, self-host on your own infrastructure, or deploy via AWS, Azure, GCP, Google Cloud, DigitalOcean, Snowflake, or Databricks integrations
- API-first with support for RAG workflows and agentic AI patterns, including a Query Agent
- SOC 2 Type II and HIPAA compliant for enterprise and regulated workloads
Weaviate is founded in 2016 and is actively maintained as an open-source project with a freemium cloud tier.
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