Weaviate — AI Vector Database

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What is Weaviate?

Weaviate is an open-source vector database that simplifies the development of AI applications. It performs vector and hybrid search operations, connects seamlessly with machine learning models, and maintains strict data privacy protocols to help developers build and scale AI capabilities faster.

What sets Weaviate apart?

Weaviate distinguishes itself through multi-tenant architecture that allows businesses to isolate data per client while maintaining search performance across millions of records. The database's hybrid search combines vector similarity with traditional keyword methods, giving developers precise control over result relevance for both text and image queries. Its active open-source community and flexible deployment options make Weaviate ideal for teams seeking to build production-ready AI applications without vendor lock-in.

Weaviate Use Cases

Semantic search applications
AI model integrations
Recommendation systems
Enterprise AI deployment
RAG chatbots

Who uses Weaviate?

Machine Learning Engineers Data Analysts Business Analysts Database Administrators (DBA) Applied Scientists Software Engineers Data Engineers Data Scientists

Features and Benefits

Vector Search
Performs lightning-fast vector similarity search over data objects, even with complex filters applied to deliver more accurate results.
Hybrid Search
Combines vector search and BM25 keyword search to improve semantic understanding and accuracy without additional overhead.
Multi-Tenant Architecture
Scales horizontally with strict resource isolation between tenants, allowing millions of separate data environments within a single deployment.
Model Integration
Connects directly to 20+ machine learning models and frameworks, enabling quick adoption and testing of new models as the ecosystem evolves.
Flexible Deployment
Runs as a self-hosted database, managed service, or Kubernetes package in your VPC to match specific security and compliance requirements.

Weaviate Pros and Cons

Pros

Quick setup and integration with minimal technical overhead
Excellent customer support with responsive team on Slack
High performance and reliability for vector search at scale
Flexible deployment options across cloud, local, and on-premise
Strong community support and regular product improvements

Cons

Basic and limited admin interface/dashboard functionality
Documentation lacks sufficient examples and clarity
Steep learning curve for advanced features
Occasional stability issues with data corruption risks

Pricing

Free Trial

Standard Support (Serverless Cloud) $25/mo

Usage charge: USD 0.095 per 1M vector dimensions stored per month
Email-based support during business hours
Response times: Severity 1: 1 business day, Severity 2: 2 business days, Severity 3: 3 business days, Severity 4: 5 business days

Professional Support (Serverless Cloud) $135/mo

Usage charge: USD 0.145 per 1M vector dimensions stored per month
24/7 email support with phone escalation for Severity 1 and 2 incidents
Response times: Severity 1: 4 hours, Severity 2: 8 hours, Severity 3: 1 business day, Severity 4: 2 business days

Business Critical Support (Serverless Cloud) $450/mo

Usage charge: USD 0.175 per 1M vector dimensions stored per month
24/7 support via email and telephone hotline for escalations
Response times: Severity 1: 1 hour, Severity 2: 4 hours, Severity 3: 8 hours, Severity 4: 1 business day

Enterprise Cloud Price not available