Weaviate
by Weaviate B.V.
The AI-native, open-source vector database developers love.
Weaviate is an open-source, AI-native vector database that stores objects and vectors together, enabling vector, keyword, and hybrid search with built-in vectorization, multi-tenancy, and RAG capabilities for production AI applications.
At a Glance
- Category
- Infrastructure & Cloud
- Pricing
- Free, Usage-based, Subscription, Contact for pricing
- Target Market
- Enterprise Developers, Data Scientists, ML Engineers, DevOps / MLOps Engineers, CTOs
- Founded
- 2019
- Headquarters
- Amsterdam, Netherlands
- Customers
- 20M+ open-source downloads; thousands of customers
Key Features
- ✓AI-native vector database
Stores objects and their vector embeddings together in one Go-based system, usable as a primary database for AI applications.
- ✓Hybrid search
Combines BM25 keyword search with vector search using customizable weighting for higher-quality, more relevant results.
- ✓Built-in vectorization
Automatically generates embeddings at import via native Weaviate Embeddings or 20+ third-party model integrations, with no separate pipeline required.
- ✓Multi-tenancy
First-class tenant isolation that scales to millions of tenants in a single instance, ideal for multi-tenant SaaS.
- ✓Query Agent and agent tooling
Managed RAG via the Query Agent plus agent memory (Engram), enabling agentic retrieval over Weaviate Cloud collections.
- ✓Flexible deployment
Open-source (BSD-3) for self-hosting via Docker or Kubernetes, plus managed Weaviate Cloud and bring-your-own-cloud (BYOC) options.
Capabilities
Use Cases
- •Retrieval-augmented generation
Store and retrieve embeddings to ground LLM responses with relevant context for accurate AI-native applications.
- •Semantic and hybrid search
Search across documents, images, audio, and video by combining vector similarity with keyword matching.
- •Multi-tenant SaaS data isolation
Serve many customers from one cluster with per-tenant partitions while controlling cost and maintaining performance.
Ideal For
Best For
- ✓Building RAG and semantic search on unstructured data
- ✓Multi-tenant SaaS applications needing per-customer data isolation
- ✓Self-hosted or hybrid vector search deployments under an open-source license
Integrations
Deployment
Market & Ratings
20M+ open-source downloads; thousands of customers
Market Analysis
Pros
- ✓Open-source and free to self-host (BSD-3)
- ✓Flexible deployment: self-hosted, managed cloud, or BYOC
- ✓Strong hybrid search and built-in vectorization
- ✓Excellent multi-tenancy for SaaS use cases
- ✓Active developer community and praised technical support
Cons
- ✗Self-hosting requires operational effort and tuning at scale
- ✗Managed cloud pricing model (per vector dimension) can be complex to estimate
- ✗Some users report setup friction and inconsistencies at large scale
Pricing
Open Source (Self-hosted)
$0
- ✓BSD-3 licensed, free software
- ✓Self-host via Docker or Kubernetes
- ✓Pay only your own infrastructure costs
- ✓Full core database features
- ✓Community support
Free Sandbox
$0
- ✓14-day trial cluster on Weaviate Cloud
- ✓Community support
- ✓Evaluation and prototyping
Flex
From $45/mo
- ✓Pay-as-you-go managed cloud
- ✓All core database features
- ✓Built-in RBAC
- ✓AI-native Embeddings and Agents
- ✓99.5% uptime on Shared Cloud
- ✓Automated upgrades
Plus
From $280/mo
- ✓Everything in Flex
- ✓Annual commitment options
- ✓Enhanced security
- ✓Stronger SLAs (99.9% uptime)
- ✓Choice of Shared or Dedicated deployments
Premium
Contact for pricing
- ✓Dedicated infrastructure or BYOC
- ✓Business-critical SLAs (99.95% uptime)
- ✓Priority response
- ✓Highest security and compliance (including HIPAA)
Weaviate OSS is free under the BSD-3 license (you pay only infrastructure). Weaviate Cloud restructured pricing in October 2025 to bill on vector dimensions stored, object storage, and backup storage; the Flex entry tier starts at $45/mo (older $25/mo Serverless tier was retired).
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